WO2016173223A1 - 用于确定用户体验及辅助确定用户体验的方法和装置 - Google Patents

用于确定用户体验及辅助确定用户体验的方法和装置 Download PDF

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Publication number
WO2016173223A1
WO2016173223A1 PCT/CN2015/092961 CN2015092961W WO2016173223A1 WO 2016173223 A1 WO2016173223 A1 WO 2016173223A1 CN 2015092961 W CN2015092961 W CN 2015092961W WO 2016173223 A1 WO2016173223 A1 WO 2016173223A1
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Prior art keywords
analyzed
user
user experience
determining
experience information
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PCT/CN2015/092961
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English (en)
French (fr)
Inventor
矫萍萍
王笑晓
黄硕
唐萌萌
曾俊梅
陈浩
万东海
魏君颖
贺依鸣
王大力
张金
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Baidu Online Network Technology Beijing Co Ltd
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Baidu Online Network Technology Beijing Co Ltd
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Publication of WO2016173223A1 publication Critical patent/WO2016173223A1/zh
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Ceased legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment

Definitions

  • the present invention relates to the field of computers, and in particular, to a method and apparatus for determining a user experience and assisting in determining a user experience.
  • a method for determining a user experience comprises the following steps:
  • an apparatus for determining a user experience comprising:
  • a method for assisting in determining a user experience on a user equipment side includes:
  • an apparatus for assisting in determining a user experience at a user equipment side comprising:
  • the operation recording means for determining user experience information of the object to be analyzed.
  • the present invention determines an operation record of an object to be analyzed by a user, and determines an operation feature of the object to be analyzed by the user based on the operation record, and then determines a user of the object to be analyzed based on the operation feature. Experiencing the information, thus realizing the automatic analysis and determination of the user experience, avoiding the inefficiency, inconvenient operation, or artificial or subjective caused by the artificial analysis of the prior art through manual observation, questionnaire survey, user feedback, etc. Problems such as deviations in results caused by factors. Compared with the prior art, the invention has higher efficiency and the analysis result is more objective.
  • FIG. 1 shows a flow chart of a method for determining a user experience, in accordance with an embodiment of the present invention
  • FIG. 2 illustrates a flow diagram of a method for assisting in determining a user experience at a user equipment side, in accordance with an embodiment of another aspect of the present invention
  • FIG. 3 shows a schematic diagram of an apparatus for determining a user experience, in accordance with an embodiment of the present invention
  • FIG. 4 shows a schematic diagram of an apparatus for assisting in determining a user experience at a user equipment side, in accordance with an embodiment of still another aspect of the present invention.
  • Computer device also referred to as “computer” in the context, is meant an intelligent electronic device that can perform predetermined processing, such as numerical calculations and/or logical calculations, by running a predetermined program or instruction, which can include a processor and The memory is executed by the processor to execute a predetermined process pre-stored in the memory to execute a predetermined process, or is executed by hardware such as an ASIC, an FPGA, a DSP, or the like, or a combination of the two.
  • Computer devices include, but are not limited to, servers, personal computers, notebook computers, tablets, smart phones, and the like.
  • the computer device includes a user device and a network device.
  • the user equipment includes, but is not limited to, a computer, a smart phone, a PDA, etc.
  • the network device includes but is not limited to a single network server, a server group composed of multiple network servers, or a cloud computing based computer Or a cloud composed of a network server, wherein cloud computing is a type of distributed computing, a super virtual computer composed of a group of loosely coupled computers.
  • the computer device can be operated separately to implement the present invention, and can also access the network and operate through interaction with other computer devices in the network. this invention.
  • the network in which the computer device is located includes, but is not limited to, the Internet, a wide area network, a metropolitan area network, a local area network, a VPN network, and the like.
  • the user equipment, the network equipment, the network, and the like are merely examples, and other existing or future possible computer equipment or networks, such as those applicable to the present invention, are also included in the scope of the present invention. It is included here by reference.
  • FIG. 1 is a flow chart of a method for determining a user experience, in accordance with an embodiment of an aspect of the present invention.
  • the method in this embodiment can be implemented by using a user equipment and a network device.
  • the user equipment includes, but is not limited to, a PC, a tablet, a smart phone, a PDA, and the like.
  • the network device includes, but is not limited to, a single network server, a server group composed of multiple network servers, or a cloud computing-based cloud composed of a large number of computers or network servers, wherein the cloud computing is a kind of distributed computing.
  • a super virtual computer consisting of a group of loosely coupled computers.
  • the user equipment is only an example, and other existing or future network equipment and user equipment may be applicable to the present invention, and are also included in the scope of the present invention and are included in the reference. this.
  • step S11 an operation record of the user's operation of the object to be analyzed is acquired.
  • the object to be analyzed means an object that will analyze its user experience to get its user experience information.
  • the object to be analyzed can be any software related object, such as a software interface, a web page, and the like. It should be understood by those skilled in the art that the above description of the object to be analyzed is merely an example, and any object suitable for the principles of the present invention is incorporated herein by reference.
  • the operation record of the user operating the object to be analyzed means a record of the operation performed by the user through the input device to analyze the object.
  • the operation record may be, for example, a track record of the input device when the user operates the object to be analyzed through the input device, such as a mouse track record or the like.
  • the operation record may also be, for example, an input record of the input device when the user operates the object to be analyzed through the input device, such as a mouse click input record, a keyboard input record. Wait.
  • the operation record may also include time information of the user's operation, specific location information of the operation, and the like.
  • the input device includes any type of device that can be used for input, such as a mouse, a keyboard, a touch screen, and the like.
  • the operation record of the user to be analyzed by the file system, the specific interface, or the network may be acquired.
  • step S12 based on the operation record, the user is determined to operate the operation feature of the object to be analyzed.
  • the operational characteristics may include at least one of the following:
  • the user operates a trajectory deviation between the trajectory of the object to be analyzed and a predetermined trajectory.
  • the area means a specific range of positions in the object to be analyzed.
  • the area may be a specific element in the webpage, such as a read-only text box, and the operation feature of the user to operate the object to be analyzed may be the number of clicks of the user to click the read-only text box.
  • the input area means an area that can be input by the user.
  • the input area may be an input text box in the webpage, and the number of times the user inputs the input operation in the same input area of the object to be analyzed may be the input text box of the user. The number of inputs for the input operation.
  • the operation duration of the user operating the object to be analyzed refers to the time that the user continues between the start of the operation of the object to be analyzed until the user ends the operation of the analysis object.
  • the trajectory deviation between the trajectory of the object to be analyzed and the predetermined trajectory of the object to be analyzed refers to the difference between the trajectories.
  • a trajectory can consist of a series of coordinate points or a range of coordinate point positions.
  • the coordinate point position of each operation of the user is recorded, and the coordinate point position of each operation forms a user operation.
  • the predetermined trajectory may record the coordinate point position or the position range of each operation by, for example, operating the object to be analyzed in a superior manner, and the coordinate point position or the position range of each operation forms a predetermined trajectory of the object to be analyzed.
  • the difference between the trajectories can be obtained by sequentially comparing each coordinate point in the trajectory of the object to be analyzed by the user with each coordinate point in the predetermined trajectory of the object to be analyzed. For example, when the positions of the two coordinate points of the comparison are the same or similar, or when the position of the coordinate point of the comparison falls within the range of the coordinate point position of another alignment, the difference can be considered small. On the contrary, it is considered that the gap is large. It should be understood by those skilled in the art that the description of the trajectory and the trajectory deviation is merely exemplary and not limiting, and various other implementations are possible without departing from the spirit or scope of the invention, and herein.
  • the operation feature of the user to operate the object to be analyzed may be determined by the track record of the input device included in the operation record acquired in step S11 and/or the input record of the input device.
  • the number of clicks of the user clicking on the same area in the object to be analyzed can be obtained by analyzing the input record and/or the track record of the input device included in the operation record. It is also possible to obtain an input count of the input operation performed by the user in the same input area of the object to be analyzed by analyzing the input record and/or the track record of the input device included in the operation record. It is also possible to obtain the operation duration of the user to operate the object to be analyzed by analyzing the time information in the operation record. Alternatively, the trajectory of the object to be analyzed may be obtained by the user by analyzing the input record and/or the track record of the input device included in the operation record. The trajectory is compared with the predetermined trajectory of the object to be analyzed according to the method described above to obtain a trajectory deviation between the two.
  • step S13 user experience information of the object to be analyzed may be determined based on the above operational features.
  • the number of clicks determines the user experience information of the object to be analyzed. Specifically, the number of clicks may be compared with a predetermined threshold to determine the user experience information. For example, when the number of clicks exceeds a predetermined threshold, the object to be analyzed may have a potential problem affecting the operation of the user, and then the user experience of the object to be analyzed may be determined to be poor. For each area of the object to be analyzed, when the number of clicks of the user clicking the area does not exceed the predetermined threshold, the user experience of the object to be analyzed may be considered normal.
  • a weight may also be set, and the weighted average value of the user clicks on each area is compared with a predetermined threshold to obtain user experience information of the object to be analyzed.
  • the user experience information of the object to be analyzed may be determined based on the number of times the user performs an input operation within the same input area of the object to be analyzed. Specifically, the number of inputs may be compared with a predetermined threshold to determine the user experience information. For example, when the number of inputs exceeds a predetermined threshold, the object to be analyzed may have a potential problem affecting the operation of the user, and then the user experience of the object to be analyzed may be determined to be poor. For each input area of the object to be analyzed, when the number of input operations of the input operation performed by the user in the input area does not exceed the predetermined threshold, the user experience of the object to be analyzed may be considered normal.
  • a weight may also be set, and a weighted average value of the number of input times of the input operation performed by the user in each input area is compared with a predetermined threshold to obtain the above User experience information of the object to be analyzed. It should be understood by those skilled in the art that, here, the relevant description of determining the user experience information of the object to be analyzed based on the number of times the user performs an input operation in the same input area of the object to be analyzed is merely exemplary rather than limiting. There are other various implementations without departing from the spirit or scope of the invention, and are incorporated herein by reference.
  • the user experience information of the user to operate the object to be analyzed may be determined based on an operation duration of a user operating the object to be analyzed. Specifically, can The user experience information is determined by comparing the operational duration to a predetermined threshold. For example, when the operation duration exceeds a predetermined threshold, the object to be analyzed may have a potential problem affecting the user operation, and then the user experience of the object to be analyzed may be determined to be poor. When the operation duration does not exceed the predetermined threshold, the user of the object to be analyzed may be considered to be normal.
  • the user experience information of the user to be analyzed may be determined based on a trajectory deviation between a trajectory of the object to be analyzed and a predetermined trajectory of the object to be analyzed. Specifically, the trajectory deviation may be compared with a predetermined threshold to determine the user experience information. For example, when the trajectory deviation exceeds a predetermined threshold, the object to be analyzed may have a potential problem affecting the operation of the user, and then the user experience of the object to be analyzed may be determined to be poor. When the trajectory deviation does not exceed the predetermined threshold, the user of the object to be analyzed may be considered to be normal.
  • the user experience information of the object to be analyzed may also be determined based on each user experience information determined according to the method described above. For example, according to the method described above, based on the number of clicks of the user clicking on the same area in the object to be analyzed, it is determined that the user experience information of the object to be analyzed is good; and based on the user inputting in the same input area of the object to be analyzed.
  • the user experience information of the object to be analyzed is determined to be extremely poor.
  • the user experience information of the object to be analyzed is determined to be poor according to the operation duration of the object to be analyzed. Based on the average value of the user experience information, the user experience information of the object to be analyzed is poor.
  • each user experience information may also be weighted, and the user body of the object to be analyzed is obtained through a weighted average of each user experience information. Test information. It should be understood by those skilled in the art that, here, the relevant description of determining the user experience information of the object to be analyzed based on each user experience information determined according to the method described above is merely an exemplary rather than a descriptive description. There are other various implementations without departing from the spirit or scope of the invention, and are incorporated herein by reference.
  • the user experience information of the object to be analyzed may be determined based on the number of users in which the number of clicks of the same area in the object to be analyzed exceeds the first threshold. For example, for 100 users, the number of users who click on the same area in the object to be analyzed exceeds the first threshold is 30, and the number exceeds the predetermined threshold 20. Then, the object to be analyzed has a potential problem that affects the operation of the user, so that the user experience information of the object to be analyzed is determined to be poor. On the other hand, if the number does not exceed the predetermined threshold, it may be determined that the user experience information of the object to be analyzed is normal.
  • user experience information of the object to be analyzed may be determined based on the number of users whose number of inputs exceeds a second threshold. For example, for 100 users, the number of users who perform the input operation in the same input area in the object to be analyzed exceeds the second threshold by 60, the number far exceeding the predetermined threshold 10.
  • the object to be analyzed may be considered to have a potential problem that seriously affects the operation of the user, thereby determining that the user experience information of the object to be analyzed is extremely poor. On the other hand, if the number does not exceed the predetermined threshold, it may be determined that the user experience information of the object to be analyzed is good.
  • user experience information of the object to be analyzed may be determined based on the number of users in which the operation duration exceeds a third threshold. For example, for 100 users, the number of users whose operational duration exceeds a third threshold is five, which is below a predetermined threshold of 10. Then, the object to be analyzed does not have a potential problem that affects the operation of the user, so that the user experience information of the object to be analyzed is normal. On the other hand, if the number exceeds a predetermined threshold, it may be determined that the user experience information of the object to be analyzed is poor.
  • the user experience information of the object to be analyzed may be determined based on the number of users in which the trajectory deviation exceeds a fourth threshold. For example, for 100 users, the number of users whose deviation between the trajectory of the object to be analyzed and the predetermined trajectory of the object to be analyzed exceeds the fourth threshold is 25, which is slightly more than The threshold is predetermined to be 20. Then, the object to be analyzed may be considered to have potential problems affecting the operation of the user, thereby determining that the user experience information of the object to be analyzed is a deviation. On the other hand, if the number does not exceed the predetermined threshold, it may be determined that the user experience information of the object to be analyzed is normal.
  • user experience information of the object to be analyzed may be determined based on a difference between the track records between the respective users. For example, for 100 users, each user can operate the trajectory record of the object to be analyzed for statistical analysis to obtain the difference.
  • the object to be analyzed may be considered to have factors affecting the user's operation, for example, the user is not provided with clear prompt information, so that the user performs according to his or her personal experience. The operation thus has a large difference in the operation trajectory between different users. Then, it can be determined that the user experience information of the object to be analyzed is poor.
  • user experience information of the object to be analyzed may also be determined based on the determined pieces of user experience information. For example, the user experience information may be averaged or weighted averaged to obtain user experience information of the object to be analyzed.
  • user experience information of each user operation object to be analyzed may be determined first based on respective operation characteristics of the respective users. Then, based on the user experience information of each user operating the object to be analyzed, the user experience information of the object to be analyzed is determined. For example, for 100 users, the respective operational characteristics of the 100 user operations to be analyzed may be obtained according to the method described above. And the user experience information of each user to operate the object to be analyzed is determined according to the respective operation characteristics according to the method described above. Assume that the result is that for 70 users, the user experience information of the object to be analyzed is poor; for 20 of them, the result is normal; for 10 users, the result is better.
  • the user experience information of each user may be averaged to obtain user experience information of the object to be analyzed.
  • the user experience information of the object to be analyzed is poor.
  • the user may also be assigned weights, such as different weights based on user type, or user experience values, and the like.
  • the user experience information of each user is weighted and averaged to obtain user experience information of the object to be analyzed.
  • the user experience can also be The information is below a certain threshold, for example, the number of users with poor user experience information is compared to a predetermined threshold. If the user exceeding the predetermined threshold number has poor user experience information, it is determined that the user experience information of the object to be analyzed is poor.
  • one or more error information generated by the user in the process of operating the object to be analyzed may also be acquired; and based on the operational characteristics of the user obtained according to the method described above, combined with the one or A plurality of error information is used to determine user experience information of the object to be analyzed.
  • one or more error information generated by the user in the process of operating the object to be analyzed may be obtained through a file system operation, or through a specific interface, or through a network or the like.
  • the error information may be foreground error information, such as an error operation prompt given by the system to the user.
  • the error information may also be background error information, such as various operational errors that occur in the system.
  • the user's operation characteristics and error information may be considered in combination. For example, when the user experience information determined based on the user's operation characteristics is normal, but there are multiple error information and the error level of one of the error information is serious, the user experience information of the object to be analyzed may still be considered to be poor. It should be understood by those skilled in the art that, here, the relevant description of determining the user experience information of the object to be analyzed based on the operation characteristics of the user and combining the error information is merely exemplary rather than limiting description, and various other implementations exist. This is done without departing from the spirit or scope of the invention, and is incorporated herein by reference.
  • the user experience warning information of the object to be analyzed may also be generated based on the operation feature of the user and combined with one or more error information generated by the user in the process of operating the object to be analyzed. For example, when the method according to the above is used, based on the user's operation characteristics and combined with one or more error information generated by the user in the process of operating the object to be analyzed, it is determined that the user experience information of the object to be analyzed is poor. When the user experience warning information of the object to be analyzed is generated, "warning: the user experience is poor!.
  • the user clicks to analyze The number of users whose number of clicks in the same area of the object exceeds the fifth threshold, or the number of users in which the number of inputs of the user input in the same input area of the object to be analyzed exceeds the sixth threshold, or based on the user operation to be analyzed.
  • the object to be analyzed may still be determined.
  • the user experience is poor and generates the user experience warning information of the object to be analyzed "warning: poor user experience!”.
  • the user experience difference information between the versions of the object to be analyzed may also be determined based on user experience information of each version of the object to be analyzed. Specifically, user experience information of each version of the object to be analyzed may be compared to determine user experience difference information. Through the user experience difference information, the version of the object to be analyzed with a better user experience can be compared with other versions to obtain a difference that may make the user experience better. By comparing the user experience difference information between different versions, it can be beneficial to improve the object to be analyzed to improve its user experience.
  • each threshold may be dynamically adjusted according to actual needs.
  • FIG. 2 shows a flow diagram of a method for assisting in determining a user experience at a user equipment side, in accordance with an embodiment of another aspect of the present invention.
  • step S21 the user equipment generates an operation record according to the operation of the object to be analyzed by the user, and the operation record is used to determine user experience information of the object to be analyzed.
  • the object to be analyzed means an object that will analyze its user experience to get its user experience information.
  • the object to be analyzed can be any software related object, such as software interface, webpage Wait. It should be understood by those skilled in the art that the above description of the object to be analyzed is merely an example, and any software-related object suitable for the principles of the present invention is incorporated herein by reference.
  • the operation record means a record of the operation performed by the user through the input device to analyze the object.
  • the operation record may be, for example, a track record of the input device when the user operates the object to be analyzed through the input device, such as a mouse track record or the like.
  • the operation record may also be, for example, an input record of the input device when the user operates the object to be analyzed through the input device, such as a mouse click input record, a keyboard input record, and the like.
  • the operation record may also include time information of the user's operation, specific location information of the operation, and the like.
  • the input device includes any type of device that can be used for input, such as a mouse, a keyboard, a touch screen, and the like.
  • the user equipment may generate an operation record according to an operation of the user to analyze the object, and save the operation record in, for example, a log or a database for determining user experience information of the object to be analyzed.
  • the user equipment further records one or more error information generated by the user in the process of operating the object to be analyzed for determining user experience information of the object to be analyzed.
  • the error information may be foreground error information, such as an error operation prompt given by the system to the user.
  • the error information may also be background error information generated in the user equipment or available to the user equipment, such as various operational errors occurring in the system.
  • the user equipment may save the foregoing error information in, for example, a log or a database for determining user experience information of the object to be analyzed.
  • the user equipment when the user starts operating the object to be analyzed, the user equipment starts generating an operation record; when the user ends the operation of the object to be analyzed, the user equipment ends generating the operation record.
  • the user equipment can also send an operation record of the user to the network device.
  • the user equipment may send the foregoing operation record to the network device through a specific interface with the network device or through a network.
  • FIG. 3 illustrates a schematic diagram of an apparatus for determining a user experience, in accordance with an embodiment of the present invention.
  • the device for determining a user experience includes means 31 for acquiring an operation record of a user to operate an object to be analyzed, hereinafter referred to as a first obtaining device 31; for determining that the user operates the to-be-analyzed based on the operation record Device for operating features of an object 32, hereinafter referred to as the first operational characteristic determining means 32; and means 33 for determining user experience information of the object to be analyzed based on the operational characteristics, hereinafter referred to as the first determining means 33.
  • the device in this embodiment can be implemented by using a user equipment and a network device.
  • the user equipment includes, but is not limited to, a PC, a tablet, a smart phone, a PDA, and the like.
  • the network device includes, but is not limited to, a single network server, a server group composed of multiple network servers, or a cloud computing-based cloud composed of a large number of computers or network servers, wherein the cloud computing is a kind of distributed computing.
  • a super virtual computer consisting of a group of loosely coupled computers.
  • the user equipment is only an example, and other existing or future network equipment and user equipment may be applicable to the present invention, and are also included in the scope of the present invention and are included in the reference. this.
  • the first obtaining means 31 will acquire an operation record of the user operating the object to be analyzed.
  • the object to be analyzed means an object that will analyze its user experience to get its user experience information.
  • the object to be analyzed can be any software related object, such as a software interface, a web page, and the like. It should be understood by those skilled in the art that the above description of the object to be analyzed is merely an example, and any object suitable for the principles of the present invention is incorporated herein by reference.
  • the operation record of the user operating the object to be analyzed means a record of the operation performed by the user through the input device to analyze the object.
  • the operation record may be, for example, a track record of the input device when the user operates the object to be analyzed through the input device, such as a mouse track record or the like.
  • the operation record may also be, for example, an input record of the input device when the user operates the object to be analyzed through the input device, such as a mouse click input record, a keyboard input record, and the like.
  • the operation record may also include time information of the user's operation, specific location information of the operation, and the like.
  • the input device includes any type of device that can be used for input, such as a mouse, a keyboard, a touch screen, and the like.
  • the first obtaining device 31 may acquire an operation record of the user operating the object to be analyzed by reading the file system, using a specific interface, or by using a network or the like.
  • the first operational characteristic determining means 32 will determine, based on the operational record, the operational characteristics of the user to operate the object to be analyzed.
  • the operational characteristics may include at least one of the following:
  • the user operates a trajectory deviation between the trajectory of the object to be analyzed and a predetermined trajectory.
  • the area means a specific range of positions in the object to be analyzed.
  • the area may be a specific element in the webpage, such as a read-only text box, and the operation feature of the user to operate the object to be analyzed may be the number of clicks of the user to click the read-only text box.
  • the input area means an area that can be input by the user.
  • the input area may be an input text box in the webpage, and the number of times the user inputs the input operation in the same input area of the object to be analyzed may be the input text box of the user. The number of inputs for the input operation.
  • the operation duration of the user operating the object to be analyzed refers to the time that the user continues between the start of the operation of the object to be analyzed until the user ends the operation of the analysis object.
  • the trajectory deviation between the trajectory of the object to be analyzed and the predetermined trajectory of the object to be analyzed refers to the difference between the trajectories.
  • a trajectory can consist of a series of coordinate points or a range of coordinate point positions.
  • the coordinate point position of each operation of the user is recorded, and the coordinate point position of each operation forms a trajectory of the user to operate the object to be analyzed.
  • the predetermined trajectory may record the coordinate point position or the position range of each operation by, for example, operating the object to be analyzed in a superior manner, and the coordinate point position or the position range of each operation forms a predetermined trajectory of the object to be analyzed.
  • the difference between the trajectories can be obtained by sequentially comparing each coordinate point in the trajectory of the object to be analyzed by the user with each coordinate point in the predetermined trajectory of the object to be analyzed. For example, when the positions of the two coordinate points of the comparison are the same or similar, or when the position of the coordinate point of the comparison falls within the range of the coordinate point position of another alignment, the difference can be considered small. Conversely, the gap is considered Larger. It should be understood by those skilled in the art that the description of the trajectory and the trajectory deviation is merely exemplary and not limiting, and various other implementations are possible without departing from the spirit or scope of the invention, and herein.
  • the first operation feature determining device 32 may determine, by the track record of the input device included in the operation record acquired by the first obtaining device 31 and/or the input record of the input device, the operation of the user to operate the object to be analyzed. feature.
  • the first operational characteristic determining means 32 may obtain the number of clicks by the user to click on the same area in the object to be analyzed by analyzing the input record and/or the track record of the input device included in the operation record.
  • the first operational characteristic determining means 32 can also obtain the number of inputs of the input operation by the user in the same input area of the object to be analyzed by analyzing the input record and/or the track record of the input device included in the operation record.
  • the first operational characteristic determining means 32 can also obtain the operational duration of the user's operation of the object to be analyzed by analyzing the time information in the operational record.
  • the first operating characteristic determining device 32 may also obtain a trajectory of the user to operate the object to be analyzed by analyzing an input record and/or a track record of the input device included in the operation record.
  • the first operational characteristic determining means 32 compares the trajectory with a predetermined trajectory of the object to be analyzed in accordance with the method described above to obtain a trajectory deviation between the two.
  • first operational feature determining device 32 is merely exemplary and not limiting, and various other implementations are possible without departing from the spirit or scope of the present invention. The way is included here.
  • the first determining means 33 may determine user experience information of the object to be analyzed based on the above operational characteristics.
  • the apparatus for determining user experience information of the object to be analyzed by the user based on the number of clicks which is included in the first determining means 33, is hereinafter referred to as a second determining means 331 (not shown)
  • the user experience information of the object to be analyzed may be determined based on the number of clicks of the user in the same area in the object to be analyzed.
  • the second determining means 331 may compare the number of clicks with a predetermined threshold to determine the user experience information. For example, when the number of clicks exceeds a predetermined threshold, the object to be analyzed may have a potential problem affecting the operation of the user, and the second determining means 331 may determine the The user experience of the object to be analyzed is poor.
  • the second determining means 331 may consider that the user to be analyzed has a normal experience. In an embodiment, the second determining means 331 may further set a weight for each different area of the object to be analyzed, and compare the weighted average value of the user click each area with a predetermined threshold to obtain the object to be analyzed. User experience information. It should be understood by those skilled in the art that the description of the second determining means 331 herein is for the purpose of illustration and not limitation, Included here.
  • the apparatus for determining user experience information of the object to be analyzed by the user based on the number of inputs is included in the first determining means 33, hereinafter referred to as the third determining means 332 (not It is shown that the user experience information of the object to be analyzed can be determined based on the number of times the user performs an input operation in the same input area of the object to be analyzed. Specifically, the third determining means 332 may compare the number of inputs with a predetermined threshold to determine the user experience information. For example, when the number of inputs exceeds a predetermined threshold, the object to be analyzed may have a potential problem affecting the operation of the user, and the third determining device 332 may determine that the user experience of the object to be analyzed is poor.
  • the third determining means 332 can consider that the user to be analyzed has a normal experience. In one embodiment, for each different input area of the object to be analyzed, the third determining means 332 may also set a weight and perform a weighted average of the number of inputs of the input operation by the user in each input area with a predetermined threshold. The above comparison is performed to obtain user experience information of the object to be analyzed. It should be understood by those skilled in the art that the description of the third determining device 332 is merely exemplary and not limiting, and various other implementations are possible without departing from the spirit or scope of the present invention and by way of reference. Included here.
  • the apparatus for determining, in the first determining means 33, the user experience information of the object to be analyzed by the user based on the operation duration hereinafter referred to as the fourth determining means 333 (hereinafter referred to as the fourth determining means 333) Not shown), the user experience of the user to operate the object to be analyzed may be determined based on an operation duration of a user operating the object to be analyzed. information. Specifically, the fourth determining means 333 may compare the operation duration with a predetermined threshold to determine the user experience information.
  • the object to be analyzed may have a potential problem affecting the user operation, and the fourth determining device 333 may determine that the user experience of the object to be analyzed is poor.
  • the fourth determining device 333 may consider that the user to be analyzed has a normal experience. It should be understood by those skilled in the art that the description of the fourth determining means 333 is merely exemplary and not limiting, and various other implementations are possible without departing from the spirit or scope of the invention and by way of reference. Included here.
  • the apparatus for determining the user experience information of the object to be analyzed by the user based on the trajectory deviation included in the first determining means 33 is hereinafter referred to as the fifth determining means 334 (not It is shown that the user experience information of the user to be analyzed may be determined based on a trajectory deviation between a trajectory of the object to be analyzed and a predetermined trajectory of the object to be analyzed. Specifically, the fifth determining means 334 may compare the trajectory deviation with a predetermined threshold to determine the user experience information. For example, when the trajectory deviation exceeds a predetermined threshold, the object to be analyzed may have a potential problem affecting the user's operation, and the fifth determining device 334 may determine that the user experience of the object to be analyzed is poor.
  • the fifth determining device 334 may consider that the user to be analyzed has a normal experience. It should be understood by those skilled in the art that the description of the fifth determining device 334 is merely exemplary and not limiting, and various other implementations are possible without departing from the spirit or scope of the present invention and by way of reference. Included here.
  • the first determining device 33 further includes means for determining user experience information of the object to be analyzed based on the determined pieces of user experience information, hereinafter referred to as a sixth determining device 335 (not shown) Out).
  • the sixth determining means 335 may determine user experience information of the object to be analyzed based on each piece of user experience information determined according to the method described above.
  • the first determining means 33 determines, according to the method described above, that the user experience information of the object to be analyzed is good based on the number of clicks of the same area in the object to be analyzed; based on the same identity of the object to be analyzed Entering the number of times of the input operation in the input area, determining that the user experience information of the object to be analyzed is extremely poor; determining that the user operation is based on the operation duration of the user to operate the object to be analyzed The user experience information of the object to be analyzed is poor. Then, the sixth determining means 335 can obtain that the user experience information of the object to be analyzed is poor based on the average value of the user experience information.
  • the sixth determining means 335 may further weight the user experience information, and obtain the user experience information of the object to be analyzed by using a weighted average of the user experience information. It should be understood by those skilled in the art that the description of the sixth determining means 335 is merely exemplary and not limiting, and various other implementations are possible without departing from the spirit or scope of the invention and by way of reference. Included here.
  • the first determining means 33 includes means for determining, for a plurality of users, user experience information of the object to be analyzed based on the number of users in which the number of clicks exceeds a first threshold, hereinafter referred to as A seventh determining device 336 (not shown).
  • the seventh determining means 336 may determine the user experience information of the object to be analyzed based on the number of users in which the number of clicks of the same area in the object to be analyzed exceeds the first threshold. For example, for 100 users, the number of users who click on the same area in the object to be analyzed exceeds the first threshold is 30, and the number exceeds the predetermined threshold 20.
  • the seventh determining device 336 may consider that the object to be analyzed has a potential problem that affects the operation of the user, thereby determining that the user experience information of the object to be analyzed is poor. On the other hand, if the number does not exceed the predetermined threshold, the seventh determining means 336 may determine that the user experience information of the object to be analyzed is normal.
  • the first determining means 33 includes means for determining, for a plurality of users, user experience information of the object to be analyzed based on the number of users in which the number of inputs exceeds a second threshold, Referred to as the eighth determining means 337 (not shown).
  • the eighth determining means 337 may determine the user experience information of the object to be analyzed based on the number of users whose number of inputs exceeds the second threshold. For example, for 100 users, the number of users who perform the input operation in the same input area in the object to be analyzed exceeds the second threshold by 60, the number far exceeding the predetermined threshold 10.
  • the eighth determining device 337 may consider that the object to be analyzed has a potential problem that seriously affects the operation of the user, thereby determining that the user experience information of the object to be analyzed is extremely poor. On the other hand, if the number does not exceed the predetermined threshold, the eighth determining means 337 may determine that the user experience information of the object to be analyzed is good.
  • the first determining means 33 includes means for determining, for a plurality of users, user experience information of the object to be analyzed based on the number of users in which the operation duration exceeds a third threshold, Hereinafter referred to as a ninth determining means 338 (not shown).
  • the ninth determining means 338 may determine user experience information of the object to be analyzed based on the number of users in which the operation duration exceeds a third threshold. For example, for 100 users, the number of users whose operational duration exceeds a third threshold is five, which is below a predetermined threshold of 10.
  • the ninth determining means 338 can consider that the object to be analyzed does not have a potential problem affecting the operation of the user, thereby determining that the user experience information of the object to be analyzed is normal. On the other hand, if the number exceeds the predetermined threshold, the ninth determining means 338 may determine that the user experience information of the object to be analyzed is poor.
  • the first determining means 33 includes means for determining, for a plurality of users, user experience information of the object to be analyzed based on the number of users in which the trajectory deviation exceeds a fourth threshold, Referred to as the tenth determining means 339 (not shown).
  • the tenth determining means 339 may determine user experience information of the object to be analyzed based on the number of users in which the trajectory deviation exceeds a fourth threshold. For example, for 100 users, the number of users whose deviation between the trajectory of the object to be analyzed and the predetermined trajectory of the object to be analyzed exceeds the fourth threshold is 25, which slightly exceeds the predetermined threshold 20.
  • the tenth determining device 339 may consider that the object to be analyzed may have a potential problem affecting the operation of the user, thereby determining that the user experience information of the object to be analyzed is a deviation. On the other hand, if the number does not exceed the predetermined threshold, the tenth determining means 339 may determine that the user experience information of the object to be analyzed is normal. Further, in still another embodiment, the first determining means 33 includes means for determining, for a plurality of users, user experience information of the object to be analyzed based on a difference between the track records between the respective users. The device, hereinafter referred to as the eleventh determining device 3310 (not shown).
  • the eleventh determining means 3310 may determine user experience information of the object to be analyzed based on a difference between the track records among the respective users. For example, for 100 users, the eleventh determining means 3310 may perform statistical analysis on the trajectory records of the respective objects to be analyzed by the respective users to derive the difference. When the statistical analysis result is that the difference between the user trajectories is greater than a predetermined threshold, the eleventh determining device 3310 may consider that the object to be analyzed may have factors affecting user operations, such as There are clear prompts for the user, so that the user can operate according to his or her personal experience, so that the operation trajectory between different users is quite different. Then, the eleventh determining means 3310 can determine that the user experience information of the object to be analyzed is poor.
  • the first determining device 33 includes means for determining, for a plurality of users, user experience information of the object to be analyzed based on the determined pieces of user experience information, hereinafter referred to as the twelfth A device 3311 (not shown) is determined.
  • the twelfth determining means 3311 may further determine user experience information of the object to be analyzed based on the determined pieces of user experience information. For example, the twelfth determining means 3311 may average the user experience information described above or perform a weighted average to obtain user experience information of the object to be analyzed.
  • the first determining means 33 includes means for determining, for a plurality of users, respective user experience information of the respective objects to be analyzed based on the respective operating characteristics of the respective users, hereinafter referred to as shorthand a thirteenth determining device 3312 (not shown); and means for determining user experience information of the object to be analyzed based on respective user experience information of each user to operate the object to be analyzed, hereinafter referred to as the fourteenth determination Device 3313 (not shown).
  • the thirteenth determining means 3312 may first determine user experience information of each user to operate the object to be analyzed based on respective operating characteristics of the respective users.
  • the fourteenth determining means 3313 determines the user experience information of the object to be analyzed based on the user experience information of each user to be analyzed. For example, for 100 users, the thirteenth determining means 3312 can acquire the respective operational characteristics of the 100 user operations to be analyzed in accordance with the method described above. The fourteenth determining means 3313 may determine the user experience information of each user to operate the object to be analyzed based on the respective operational characteristics in accordance with the method described above. Assume that the result is that for 70 users, the user experience information of the object to be analyzed is poor; for 20 of them, the result is normal; for 10 users, the result is better.
  • the fourteenth determining means 3313 may average the user experience information of each user to obtain user experience information of the object to be analyzed. For example, in the above example, the user experience information of the object to be analyzed is poor. In one embodiment, the fourteenth determining means 3313 may also assign weights to the user, such as assigning different weights based on user type, or user experience values, and the like. Fourteenth The determining device 3313 performs weighted averaging of the user experience information of each user to obtain user experience information of the object to be analyzed. In another embodiment, the fourteenth determining means 3313 may also compare its user experience information below a certain threshold, such as the number of users with poor user experience information, to a predetermined threshold.
  • a certain threshold such as the number of users with poor user experience information
  • the fourteenth determining means 3313 determines that the user experience information of the object to be analyzed is poor. It should be understood by those skilled in the art that the description of the fourteenth determining device 3313 is merely exemplary and not limiting, and that there are other various implementations without departing from the spirit or scope of the present invention. The way is included here.
  • the first obtaining device 11 further includes means for acquiring one or more error information generated by the user in the process of operating the object to be analyzed, hereinafter referred to as the second obtaining device 111 (not shown)
  • the first determining device 11 further includes means for determining user experience information of the object to be analyzed based on the operating feature and in combination with the one or more error information, hereinafter referred to as the fifteenth determining device 1114. (not shown).
  • the second obtaining means 111 may acquire one or more error information generated by the user in the process of operating the object to be analyzed; and, the fifteenth determining means 1114 (based on the operating characteristics of the user obtained according to the method described above, and Combining the one or more error information, the user experience information of the object to be analyzed is determined.
  • the second obtaining device 111 may obtain a user operation to be analyzed through a file system operation, or through a specific interface, or through a network or the like.
  • One or more error messages generated in the process of the object wherein the error information may be foreground error information, such as an error operation prompt given by the system to the user, etc.
  • the error information may also be a background error message, such as Various operational errors and the like appearing in the system.
  • the fifteenth determining means 1114 determines the user experience information of the object to be analyzed
  • the operating characteristics and error information of the user may be considered in combination. For example, when determined based on the operating characteristics of the user User experience information is normal, however there are multiple error messages and one of the error messages If the error level is serious, the fifteenth determining device 1114 can still consider that the user experience information of the object to be analyzed is poor.
  • the relevant description for the fifteenth determining device 1114 is only an example. The invention is not limited thereto, and various other implementations are possible without departing from the spirit or scope of the invention and are hereby incorporated by reference.
  • the means for determining a user experience further comprises means for generating user experience warning information of the object to be analyzed based on the operational characteristics and in combination with the one or more error information, Hereinafter referred to as the first generating means 34 (not shown).
  • the first generating device 34 may generate the user experience warning information of the object to be analyzed based on the operation feature of the user and the one or more error information generated in the process of the user operating the object to be analyzed. For example, when the method according to the above is used, based on the user's operation characteristics and combined with one or more error information generated by the user in the process of operating the object to be analyzed, it is determined that the user experience information of the object to be analyzed is poor. The first generating device 34 may generate the user experience warning information “warning: the user experience is poor!” of the object to be analyzed.
  • the first generating device 34 may be based on the number of users in which the user clicks on the same region of the object to be analyzed exceeds a fifth threshold, or based on the same input in which the user is in the object to be analyzed The number of users who input the number of inputs in the area exceeding the sixth threshold, or the number of users based on the operation duration in which the user operates the object to be analyzed exceeds the seventh threshold, or based on the trajectory in which the user operates the object to be analyzed Generating the number of users whose trajectory deviation between predetermined trajectories of the object exceeds an eighth threshold, or based on a difference between the trajectory records between respective users; and in combination with the one or more error information, generating the User experience warning information of the object to be analyzed.
  • the first generating device 34 can still Determining the user experience of the object to be analyzed is poor and generating the user experience warning information of the object to be analyzed "warning: poor user experience!.
  • first generation device 34 is merely exemplary and not limiting, and various other implementations are possible without departing from the spirit or scope of the invention and by way of reference. Included here.
  • the means for determining a user experience further comprises means for determining user experience difference information between respective versions of the object to be analyzed based on user experience information of respective versions of the object to be analyzed,
  • the difference determining means 35 (not shown) will be referred to.
  • the difference determining means 35 may determine user experience difference information between the versions of the object to be analyzed based on user experience information of each version of the object to be analyzed. Specifically, the difference determining means 35 may compare the user experience information of each version of the object to be analyzed to determine its user experience difference information. Through the user experience difference information, the difference determining means 35 can compare the version of the object to be analyzed having a better user experience with other versions to derive a difference which may make the user experience superior. By comparing the user experience difference information between different versions, it can be beneficial to improve the object to be analyzed to improve its user experience.
  • each threshold may be dynamically adjusted according to actual needs.
  • the apparatus includes means for generating an operation record according to an operation of the user to analyze the object, the operation recording means 41 for determining user experience information of the object to be analyzed, hereinafter referred to as the first record generating means 41.
  • the first record generating means 41 generates an operation record for determining the user experience information of the object to be analyzed according to the operation of the object to be analyzed by the user.
  • the object to be analyzed means an object that will analyze its user experience to get its user experience information.
  • the object to be analyzed can be any software related object, such as a software interface, a web page, and the like. It should be understood by those skilled in the art that the above description of the object to be analyzed is merely an example, and any software-related object suitable for the principles of the present invention is incorporated herein by reference.
  • the operation record means a record of the operation performed by the user through the input device to analyze the object.
  • the operation record may be, for example, a track record of the input device when the user operates the object to be analyzed through the input device, such as a mouse track record or the like.
  • the operation record may also be, for example, an input record of the input device when the user operates the object to be analyzed through the input device, such as a mouse click input record, a keyboard input record, and the like.
  • the operation record may also include time information of the user's operation, specific location information of the operation, and the like.
  • the input device includes any type of device that can be used for input, such as a mouse, a keyboard, a touch screen, and the like.
  • the first record generating device 41 may generate an operation record according to an operation of the user to analyze the object, and save the operation record in, for example, a log or a database for determining user experience information of the object to be analyzed.
  • the means for assisting in determining the user experience at the user equipment side further comprises recording one or more error messages generated during the user operation of the object to be analyzed for determining the
  • the device of the user experience information of the object to be analyzed is hereinafter referred to as an error recording device 42 (not shown).
  • the error recording device 42 records one or more error information generated by the user in the process of operating the object to be analyzed for determining user experience information of the object to be analyzed.
  • the error information may be foreground error information, such as an error operation prompt given by the system to the user.
  • the error message may also be background error information that is generated in the user device or that is erroneously recorded by the device 42, such as various operational errors that occur in the system.
  • the error recording device 42 may save the above error information in, for example, a log or a database for determining user experience information of the object to be analyzed.
  • the first record generating means 41 when the user starts operating the object to be analyzed, the first record generating means 41 starts generating an operation record; when the user finishes operating the object to be analyzed, the first record generating means 41 ends generating the operation record.
  • the means for assisting in determining the user experience at the user equipment side further comprises means for transmitting the operational record of the user to the network device, hereinafter referred to as transmitting means 43 (not shown).
  • the transmitting device 43 can transmit the operation record of the user to the network device. Specifically, the transmitting device 43 can transmit the above operation record to the network device through a specific interface with the network device or through the network.
  • the present invention can be implemented in software and/or a combination of software and hardware.
  • the various devices of the present invention can be implemented using an application specific integrated circuit (ASIC) or any other similar hardware device.
  • the software program of the present invention may be executed by a processor to implement the steps or functions described above.
  • the software program (including related data structures) of the present invention can be stored in a computer readable recording medium such as a RAM memory, a magnetic or optical drive or a floppy disk and the like.
  • some of the steps or functions of the present invention may be implemented in hardware, for example, as a circuit that cooperates with a processor to perform various steps or functions.
  • CLAIMS 1 A method for determining a user experience, wherein the method comprises:
  • the user operates a trajectory deviation between the trajectory of the object to be analyzed and the predetermined trajectory of the object to be analyzed.
  • step of determining user experience information of the object to be analyzed based on the operational characteristic comprises at least one of the following:
  • the step of determining the user experience information of the object to be analyzed based on the operating feature further includes:
  • step of determining user experience information of the object to be analyzed based on the operational characteristic comprises at least one of the following:
  • the determining, according to the operation feature, the user experience letter of the object to be analyzed also include:
  • the step of determining the user experience information of the object to be analyzed based on the operating feature further includes:
  • step of generating the user experience alert information of the object to be analyzed based on the operational feature and in combination with the one or more error information comprises at least one of the following :
  • a method for assisting in determining a user experience at a user equipment side comprising:
  • step of generating an operation record according to an operation of the user to analyze the object further comprises:
  • An apparatus for determining a user experience comprising:
  • the user operates a trajectory deviation between the trajectory of the object to be analyzed and the predetermined trajectory of the object to be analyzed.
  • the means for determining user experience information of the object to be analyzed based on the operational characteristic comprises at least one of the following:
  • the device for determining the user experience information of the object to be analyzed based on the operation feature further includes:
  • the device for determining the user experience information of the object to be analyzed based on the operation feature further includes:
  • the device for determining the user experience information of the object to be analyzed based on the operation feature further includes:
  • An apparatus for assisting in determining a user experience at a user equipment side comprising:
  • the operation recording means for determining user experience information of the object to be analyzed.

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Abstract

本发明提供了一种用于确定用户体验以及辅助确定用户体验的方法和装置。其中，该方法包括以下步骤：获取用户操作待分析对象的操作记录；基于所述操作记录，确定所述用户操作所述待分析对象的操作特征；基于所述操作特征，确定所述待分析对象的用户体验信息。根据本发明的方案实现了对于用户体验的自动分析及确定，避免了现有技术通过人工观察、问卷调查、用户反馈等人为方式来进行分析所导致的效率低下，操作不方便，或因为人为或主观因素所造成的结果偏差等问题。与现有技术相比，本发明具有更高的效率，并且分析结果也更加客观。

Description

用于确定用户体验及辅助确定用户体验的方法和装置
相关申请的交叉引用
本申请享有2015年04月30日提交的专利申请号为201510218948.9、名称为“用于确定用户体验及辅助确定用户体验的方法和装置”的中国专利申请的优先权，该在先申请的内容以引用方式合并于此。
技术领域
本发明涉及计算机领域，尤其涉及一种用于确定用户体验及辅助确定用户体验的方法和装置。
背景技术
现有技术中，当需要确定软件产品的用户体验时，常规的方法是通过人工观察、问卷调查、用户反馈来进行。然而常规的方法存在效率低下，操作不方便等问题，也可能因为人为或主观因素等造成结果的偏差。因此，如何自动分析并确定用户体验信息是一个需要解决的问题。
发明内容
本发明的目的是提供一种用于确定用户体验的方法和装置以及一种用于辅助确定用户体验的方法和装置。
根据本发明的一个方面，提供一种用于确定用户体验的方法，其中，该方法包括以下步骤：
-获取用户操作待分析对象的操作记录；
-基于所述操作记录，确定所述用户操作所述待分析对象的操作特征；
-基于所述操作特征，确定所述待分析对象的用户体验信息。
根据本发明的另一个方面，提供一种用于确定用户体验的装置，其中，该装置包括：
-用于获取用户操作待分析对象的操作记录的装置；
-用于基于所述操作记录，确定所述用户操作所述待分析对象的操作特征的装置；
-用于基于所述操作特征，确定所述待分析对象的用户体验信息的装置。
根据本发明的又一个方面，提供一种用于在用户设备端用于辅助确定用户体验的方法，其中，该方法包括：
-根据用户对待分析对象的操作，生成操作记录，该操作记录用于确定所述待分析对象的用户体验信息。
根据本发明的再一个方面，提供一种用于在用户设备端用于辅助确定用户体验的装置，其中，该装置包括：
-用于根据用户对待分析对象的操作，生成操作记录，该操作记录用于确定所述待分析对象的用户体验信息的装置。
与现有技术相比，本发明通过获取用户操作待分析对象的操作记录，并基于该操作记录，确定用户操作该待分析对象的操作特征，然后基于该操作特征，确定该待分析对象的用户体验信息，从而实现了对于用户体验的自动分析及确定，避免了现有技术通过人工观察、问卷调查、用户反馈等人为方式来进行分析所导致的效率低下，操作不方便，或因为人为或主观因素所造成的结果偏差等问题。与现有技术相比，本发明具有更高的效率，并且分析结果也更加客观。
附图说明
通过阅读参照以下附图所作的对非限制性实施例所作的详细描述，本发明的其它特征、目的和优点将会变得更明显：
图1示出根据本发明一个方面的实施例的用于确定用户体验的方法的流程图；
图2示出根据本发明另一个方面的实施例的在用户设备端用于辅助确定用户体验的方法的流程图；
图3示出根据本发明又一个方面的实施例的用于确定用户体验的装置的示意图；
图4示出根据本发明再一个方面的实施例的在用户设备端用于辅助确定用户体验的装置的示意图。
附图中相同或相似的附图标记代表相同或相似的部件。
具体实施方式
在更加详细地讨论示例性实施例之前应当提到的是，一些示例性实施例被描述成作为流程图描绘的处理或方法。虽然流程图将各项操作描述成顺序的处理，但是其中的许多操作可以被并行地、并发地或者同时实施。此外，各项操作的顺序可以被重新安排。当其操作完成时所述处理可以被终止，但是还可以具有未包括在附图中的附加步骤。所述处理可以对应于方法、函数、规程、子例程、子程序等等。
在上下文中所称“计算机设备”，也称为“电脑”，是指可以通过运行预定程序或指令来执行数值计算和/或逻辑计算等预定处理过程的智能电子设备，其可以包括处理器与存储器，由处理器执行在存储器中预存的存续指令来执行预定处理过程，或是由ASIC、FPGA、DSP等硬件执行预定处理过程，或是由上述二者组合来实现。计算机设备包括但不限于服务器、个人电脑、笔记本电脑、平板电脑、智能手机等。
所述计算机设备包括用户设备与网络设备。其中，所述用户设备包括但不限于电脑、智能手机、PDA等；所述网络设备包括但不限于单个网络服务器、多个网络服务器组成的服务器组或基于云计算(Cloud Computing)的由大量计算机或网络服务器构成的云，其中，云计算是分布式计算的一种，由一群松散耦合的计算机集组成的一个超级虚拟计算机。其中，所述计算机设备可单独运行来实现本发明，也可接入网络并通过与网络中的其他计算机设备的交互操作来实现 本发明。其中，所述计算机设备所处的网络包括但不限于互联网、广域网、城域网、局域网、VPN网络等。
需要说明的是，所述用户设备、网络设备和网络等仅为举例，其他现有的或今后可能出现的计算机设备或网络如可适用于本发明，也应包含在本发明保护范围以内，并以引用方式包含于此。
后面所讨论的方法(其中一些通过流程图示出)可以通过硬件、软件、固件、中间件、微代码、硬件描述语言或者其任意组合来实施。当用软件、固件、中间件或微代码来实施时，用以实施必要任务的程序代码或代码段可以被存储在机器或计算机可读介质(比如存储介质)中。(一个或多个)处理器可以实施必要的任务。
这里所公开的具体结构和功能细节仅仅是代表性的，并且是用于描述本发明的示例性实施例的目的。但是本发明可以通过许多替换形式来具体实现，并且不应当被解释成仅仅受限于这里所阐述的实施例。
应当理解的是，虽然在这里可能使用了术语“第一”、“第二”等等来描述各个单元，但是这些单元不应当受这些术语限制。使用这些术语仅仅是为了将一个单元与另一个单元进行区分。举例来说，在不背离示例性实施例的范围的情况下，第一单元可以被称为第二单元，并且类似地第二单元可以被称为第一单元。这里所使用的术语“和/或”包括其中一个或更多所列出的相关联项目的任意和所有组合。
应当理解的是，当一个单元被称为“连接”或“耦合”到另一单元时，其可以直接连接或耦合到所述另一单元，或者可以存在中间单元。与此相对，当一个单元被称为“直接连接”或“直接耦合”到另一单元时，则不存在中间单元。应当按照类似的方式来解释被用于描述单元之间的关系的其他词语(例如“处于...之间”相比于“直接处于...之间”，“与...邻近”相比于“与...直接邻近”等等)。
这里所使用的术语仅仅是为了描述具体实施例而不意图限制示例性实施例。除非上下文明确地另有所指，否则这里所使用的单数形式“一个”、“一项”还意图包括复数。还应当理解的是，这里所使 用的术语“包括”和/或“包含”规定所陈述的特征、整数、步骤、操作、单元和/或组件的存在，而不排除存在或添加一个或更多其他特征、整数、步骤、操作、单元、组件和/或其组合。
还应当提到的是，在一些替换实现方式中，所提到的功能/动作可以按照不同于附图中标示的顺序发生。举例来说，取决于所涉及的功能/动作，相继示出的两幅图实际上可以基本上同时执行或者有时可以按照相反的顺序来执行。
下面结合附图对本发明作进一步详细描述。
图1为根据本发明一个方面的实施例的用于确定用户体验的方法的流程图。
其中，本实施例的方法可以通过用户设备以及网络设备来实现。所述用户设备包括但不限于PC机、平板电脑、智能手机、PDA等。所述网络设备包括但不限于单个网络服务器、多个网络服务器组成的服务器组或基于云计算(Cloud Computing)的由大量计算机或网络服务器构成的云，其中，云计算是分布式计算的一种，由一群松散耦合的计算机集组成的一个超级虚拟计算机。
需要说明的是，所述用户设备仅为举例，其他现有的或今后可能出现的网络设备和用户设备如可适用于本发明，也应包含在本发明保护范围以内，并以引用方式包含于此。
首先，在步骤S11中，将获取用户操作待分析对象的操作记录。
此处，待分析对象意指将分析其用户体验以得到其用户体验信息的对象。待分析对象可以为任意软件相关对象，例如软件界面、网页等。本领域技术人员应理解，上述对于待分析对象的描述仅为举例，任何适用于本发明原理的对象均以引用的方式包含于此。
此处，用户操作待分析对象的操作记录意指用户通过输入设备对待分析对象所进行的操作的记录。操作记录可以为例如用户通过输入设备来操作待分析对象时，该输入设备的轨迹记录，例如鼠标轨迹记录等。操作记录还可以为例如用户通过输入设备来操作待分析对象时，该输入设备的输入记录，例如鼠标点击输入记录、键盘输入记录 等。此外，操作记录中还可以包括用户进行操作的时间信息，操作的具体位置信息等。此处，输入设备包括鼠标、键盘、触摸屏等任何类型的可用于输入的设备。
具体地，可以通过读取文件系统、通过特定接口或通过网络等方式来获取用户操作待分析对象的操作记录。
接着，在步骤S12中，将基于该操作记录，确定该用户操作该待分析对象的操作特征。
此处，操作特征可以包括以下至少任一项：
-所述用户点击所述待分析对象中的同一区域的点击次数；
-所述用户在所述待分析对象的同一输入区域内进行输入操作的输入次数；
-所述用户操作所述待分析对象的操作持续时间；
-所述用户操作所述待分析对象的轨迹与预定轨迹之间的轨迹偏差。
其中，区域意指待分析对象中的某特定位置范围。例如，当待分析对象为网页时，区域可以为该网页中的特定元素，例如只读文本框，则用户操作该待分析对象的操作特征可以为该用户点击该只读文本框的点击次数。
此处，输入区域意指能够供用户进行输入操作的区域。例如，当待分析对象为网页时，输入区域可以为该网页中的某输入文本框，则用户在该待分析对象的同一输入区域内进行输入操作的输入次数可以为该用户在该输入文本框中进行输入操作的输入次数。
此处，用户操作待分析对象的操作持续时间指用户在开始对该待分析对象进行操作至该用户结束对该分析对象的操作之间所持续的时间。
此处，用户操作该待分析对象的轨迹与该待分析对象的预定轨迹之间的轨迹偏差指轨迹之间的差距。轨迹可以由一系列坐标点或坐标点位置范围所构成。当用户对该待分析对象进行操作时，记录该用户各次操作的坐标点位置，则各次操作的坐标点位置形成了用户操作该 待分析对象的轨迹。预定轨迹可以通过例如以较优方式来操作该待分析对象时，记录各次操作的坐标点位置或位置范围，则各次操作的坐标点位置或位置范围形成了该待分析对象的预定轨迹。可以通过将用户操作该待分析对象的轨迹中的各个坐标点按顺序与该待分析对象的预定轨迹中的各个坐标点进行比较来得出轨迹之间的差距。例如，当比对的两个坐标点位置相同或相近，或当比对的坐标点位置落在另一比对的坐标点位置范围内时，可认为差距较小。反之，则认为差距较大。本领域技术人员应理解，此处，对于轨迹及轨迹偏差的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
具体地，可以通过在步骤S11中所获取的操作记录中所包括的输入设备的轨迹记录和/或输入设备的输入记录来确定该用户操作该待分析对象的操作特征。
例如，可以通过分析操作记录中所包括的输入设备的输入记录和/或轨迹记录，得到用户点击所述待分析对象中的同一区域的点击次数。也可以通过分析操作记录中所包括的输入设备的输入记录和/或轨迹记录以得到用户在所述待分析对象的同一输入区域内进行输入操作的输入次数。还可以通过分析操作记录中的时间信息以得到用户操作所述待分析对象的操作持续时间。或者也可以通过分析操作记录中所包括的输入设备的输入记录和/或轨迹记录，来得到用户操作所述待分析对象的轨迹。并将该轨迹与该待分析对象的预定轨迹按照上文所述的方法进行比对以得到两者之间的轨迹偏差。
本领域技术人员应理解，此处，对于基于操作记录来确定用户操作待分析对象的操作特征的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
接着，在步骤S13中，可基于上述操作特征，确定待分析对象的用户体验信息。
在一个实施例中，可以基于用户点击待分析对象中的同一区域的 点击次数来确定该待分析对象的用户体验信息。具体地，可以将所述点击次数与预定阈值进行比较来确定该用户体验信息。例如，当所述点击次数超过预定阈值时，则待分析对象可能存在影响用户操作的潜在问题，则可确定该待分析对象的用户体验较差。而对于该待分析对象的各个区域，当用户点击该区域的点击次数均未超出预定阈值时，则可认为该待分析对象用户体验正常。在一个实施例中，对于该待分析对象的各个不同区域，还可以设定权值，并将用户点击各个区域的加权平均值与预定阈值进行如上比较以得到该待分析对象的用户体验信息。本领域技术人员应理解，此处，对于基于用户点击待分析对象中的同一区域的点击次数来确定该待分析对象的用户体验信息的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
在另一个实施例中，可以基于用户在待分析对象的同一输入区域内进行输入操作的输入次数来确定该待分析对象的用户体验信息。具体地，可以将所述输入次数与预定阈值进行比较来确定该用户体验信息。例如，当所述输入次数超过预定阈值时，则待分析对象可能存在影响用户操作的潜在问题，则可确定该待分析对象的用户体验较差。而对于该待分析对象的各个输入区域，当用户在该输入区域进行的输入操作的输入次数均未超出预定阈值时，则可认为该待分析对象用户体验正常。在一个实施例中，对于该待分析对象的各个不同的输入区域，还可以设定权值，并将用户在各个输入区域进行输入操作的输入次数的加权平均值与预定阈值进行如上比较以得到该待分析对象的用户体验信息。本领域技术人员应理解，此处，对于基于用户在待分析对象的同一输入区域内进行输入操作的输入次数来确定该待分析对象的用户体验信息的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
在又一个实施例中，可以基于用户操作待分析对象的操作持续时间来确定所述用户操作所述待分析对象的用户体验信息。具体地，可以 将所述操作持续时间与预定阈值进行比较来确定该用户体验信息。例如，当所述操作持续时间超过预定阈值时，则待分析对象可能存在影响用户操作的潜在问题，则可确定该待分析对象的用户体验较差。而当所述操作持续时间未超出预定阈值时，则可认为该待分析对象用户体验正常。本领域技术人员应理解，此处，对于基于用户操作待分析对象的操作持续时间来确定所述用户操作所述待分析对象的用户体验信息的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
在再一个实施例中，可以基于用户操作待分析对象的轨迹与所述待分析对象的预定轨迹之间的轨迹偏差，来确定所述用户操作所述待分析对象的用户体验信息。具体地，可以将所述轨迹偏差与预定阈值进行比较来确定该用户体验信息。例如，当所述轨迹偏差超过预定阈值时，则待分析对象可能存在影响用户操作的潜在问题，则可确定该待分析对象的用户体验较差。而当所述轨迹偏差未超出预定阈值时，则可认为该待分析对象用户体验正常。本领域技术人员应理解，此处，对于基于用户操作待分析对象的轨迹与所述待分析对象的预定轨迹之间的轨迹偏差，来确定所述用户操作所述待分析对象的用户体验信息的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
在一个优选实施例中，还可以基于按照上文所述的方法所确定的各项用户体验信息，来确定该待分析对象的用户体验信息。例如，按照上文所述的方法，基于用户点击待分析对象中的同一区域的点击次数，确定出该待分析对象的用户体验信息为良好；基于用户在待分析对象的同一输入区域内进行输入操作的输入次数，确定出该待分析对象的用户体验信息为极差；基于用户操作待分析对象的操作持续时间，确定出所述用户操作所述待分析对象的用户体验信息为较差。则基于上述各项用户体验信息的平均值，可得出该待分析对象的用户体验信息为较差。在一个优选实施例中，还可以对各项用户体验信息进行加权，并通过各项用户体验信息的加权平均值来得出该待分析对象的用户体 验信息。本领域技术人员应理解，此处，对于基于按照上文所述的方法所确定的各项用户体验信息，来确定该待分析对象的用户体验信息的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
在一个实施例中，对于多个用户，可以基于其中点击待分析对象中的同一区域的点击次数超过第一阈值的用户的数量，确定所述待分析对象的用户体验信息。例如，对于100个用户，其中点击待分析对象中的同一区域的点击次数超过第一阈值的用户的数量为30个，该数量超过预定阈值20。则可认为该待分析对象存在影响用户操作的潜在问题，从而确定该待分析对象的用户体验信息为较差。反之，若该数量未超过预定阈值，则可确定该待分析对象的用户体验信息为正常。
在另一个实施例中，对于多个用户，可以基于中所述输入次数超过第二阈值的用户的数量，确定所述待分析对象的用户体验信息。例如，对于100个用户，其中在待分析对象中的同一输入区域内进行输入操作的输入次数超过第二阈值的用户的数量为60个，该数量远超过预定阈值10。则可认为该待分析对象存在严重影响用户操作的潜在问题，从而确定该待分析对象的用户体验信息为极差。反之，若该数量未超过预定阈值，则可确定该待分析对象的用户体验信息为良好。
在又一个实施例中，对于多个用户，可以基于其中所述操作持续时间超过第三阈值的用户的数量，确定所述待分析对象的用户体验信息。例如，对于100个用户，其中操作持续时间超过第三阈值的用户的数量为5个，该数量低于预定阈值10。则可认为该待分析对象不存在影响用户操作的潜在问题，从而确定该待分析对象的用户体验信息为正常。反之，若该数量超过预定阈值，则可确定该待分析对象的用户体验信息为较差。
在再一个实施例中，对于多个用户，可以基于其中所述轨迹偏差超过第四阈值的用户的数量，确定所述待分析对象的用户体验信息。例如，对于100个用户，其中操作待分析对象的轨迹与该待分析对象的预定轨迹之间的偏差超过第四阈值的用户的数量为25个，该数量略超过 预定阈值20。则可认为该待分析对象可能存在影响用户操作的潜在问题，从而确定该待分析对象的用户体验信息为偏差。反之，若该数量未超过预定阈值，则可确定该待分析对象的用户体验信息为正常。此外，在还一个实施例中，对于多个用户，可以基于其中各个用户之间的所述轨迹记录之间的差异，确定所述待分析对象的用户体验信息。例如，对于100个用户，可以将各个用户操作该待分析对象的轨迹记录进行统计分析以得出其差异。当统计分析结果为用户轨迹之间的差异大于预定阈值时，则可认为该待分析对象可能存在影响用户操作的因素，例如没有为用户提供清晰的提示信息，从而使得用户按其个人经验来进行操作从而在不同用户之间的操作轨迹差异较大。则可确定该待分析对象的用户体验信息为较差。
此外，在一个实施例中，对于多个用户，还可以基于所确定的各项用户体验信息，确定所述待分析对象的用户体验信息。例如，可以对于上述各项用户体验信息求平均值，或进行加权平均以得出所述待分析对象的用户体验信息。
在一个实施例中，对于多个用户，可以首先基于各个用户各自的操作特征，确定各个用户操作待分析对象的用户体验信息。然后，基于各个用户操作待分析对象的用户体验信息，确定该待分析对象的用户体验信息。例如，对于100个用户，可以按照上文所述的方法，获取该100个用户操作待分析对象的各自的操作特征。并可以按照上文所述的方法基于各自的操作特征，确定各个用户操作该待分析对象的用户体验信息。假定其结果为对于其中70个用户，其操作该待分析对象的用户体验信息为较差；对于其中20个用户，其结果为正常；对于其中10个用户，其结果为较好。则可以将各个用户的用户体验信息求取平均值以得出该待分析对象的用户体验信息。例如，在上例结果中，该待分析对象的用户体验信息为较差。在一个实施例中，还可以对用户分配权值，例如根据用户类型，或用户经验值等来分配不同的权值。并将各个用户的用户体验信息进行加权平均，以得出该待分析对象的用户体验信息。在另一个实施例中，还可以将其用户体验 信息低于某个阈值，例如用户体验信息较差的用户的数量与预定阈值进行比较。若超过预定阈值数量的用户均具有较差的用户体验信息，则确定该待分析对象的用户体验信息为较差。本领域技术人员应理解，此处，对于各个用户操作待分析对象的用户体验信息，确定该待分析对象的用户体验信息的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
在一个优选实施例中，还可以获取用户操作待分析对象的过程中所产生的一个或多个错误信息；并且，基于按照上文所述方法所得出的用户的操作特征，并结合该一个或多个错误信息，来确定该待分析对象的用户体验信息。具体地，可以通过文件系统操作，或通过特定接口，或通过网络等方式来获取用户操作待分析对象的过程中所产生的一个或多个错误信息。其中，所述错误信息可以为前台错误信息，例如系统向用户给出的错误操作提示等。所述错误信息也可以为后台错误信息，例如系统中所出现的各种运行错误等。当确定该待分析对象的用户体验信息时，可以结合考虑用户的操作特征与错误信息。例如，当基于用户的操作特征所确定的用户体验信息为正常，然而存在多个错误信息并且其中某个错误信息的错误等级为严重，则仍可认为该待分析对象的用户体验信息较差。本领域技术人员应理解，此处，对于基于用户的操作特征，并结合错误信息，来确定该待分析对象的用户体验信息的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
在一个实施例中，还可以基于用户的操作特征，并结合用户操作待分析对象的过程中所产生的一个或多个错误信息，生成该待分析对象的用户体验预警信息。例如，当按照上文所述的方法，基于用户的操作特征，并结合用户操作待分析对象的过程中所产生的一个或多个错误信息，确定出该待分析对象的用户体验信息为较差时，可以生成该待分析对象的用户体验预警信息“预警：用户体验较差！”。
在一个实施例中，对于多个用户，可以基于其中用户点击待分析 对象的同一区域的点击次数超过第五阈值的用户的数量，或基于其中用户在待分析对象的同一输入区域内进行输入的输入次数超过第六阈值的用户的数量，或基于其中用户操作待分析对象的操作持续时间超过第七阈值的用户的数量，或基于其中用户操作待分析对象的轨迹与该待分析对象的预定轨迹之间的轨迹偏差超过第八阈值的用户的数量，或基于其中各个用户之间的所述轨迹记录之间的差异；并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息。例如，当所述点击次数超过第五阈值的用户数量较少，然而各个用户操作该待分析对象的过程中所产生的错误信息数量较多，并且存在严重错误，则仍可确定该待分析对象的用户体验较差并生成该待分析对象的用户体验预警信息“预警：用户体验较差！”。
本领域技术人员应理解，此处，对于生成用户体验预警信息的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
在一个实施例中，还可以基于待分析对象的各个版本的用户体验信息，确定所述待分析对象的各个版本之间的用户体验差异信息。具体地，可以将待分析对象的各个版本的用户体验信息进行比较，以确定其用户体验差异信息。通过该用户体验差异信息，可以将具有较好用户体验的待分析对象的版本与其他版本进行比较，以得出其可能使得用户体验较优的区别之处。通过不同版本之间的用户体验差异信息的比较，可以有利于改进待分析对象以提高其用户体验。
本领域技术人员还应理解，上文所述的各个阈值仅为举例，并且各个阈值可以根据实际需要来动态调节。
图2示出根据本发明另一个方面的实施例的在用户设备端用于辅助确定用户体验的方法的流程图。
在步骤S21中，用户设备根据用户对待分析对象的操作，生成操作记录，该操作记录用于确定所述待分析对象的用户体验信息。
此处，待分析对象意指将分析其用户体验以得到其用户体验信息的对象。待分析对象可以为任意软件相关对象，例如软件界面、网页 等。本领域技术人员应理解，上述对于待分析对象的描述仅为举例，任何适用于本发明原理的软件相关对象均以引用的方式包含于此。
此处，操作记录意指用户通过输入设备对待分析对象所进行的操作的记录。操作记录可以为例如用户通过输入设备来操作待分析对象时，该输入设备的轨迹记录，例如鼠标轨迹记录等。操作记录还可以为例如用户通过输入设备来操作待分析对象时，该输入设备的输入记录，例如鼠标点击输入记录、键盘输入记录等。此外，操作记录中还可以包括用户进行操作的时间信息，操作的具体位置信息等。此处，输入设备包括鼠标、键盘、触摸屏等任何类型的可用于输入的设备。
具体地，用户设备可以根据用户对待分析对象的操作，生成操作记录，并将操作记录保存在例如日志或数据库中以用于确定该待分析对象的用户体验信息。
在一个实施例中，用户设备还记录用户操作所述待分析对象过程中所产生的一个或多个错误信息以用于确定所述待分析对象的用户体验信息。其中，所述错误信息可以为前台错误信息，例如系统向用户给出的错误操作提示等。所述错误信息也可以为在用户设备中所产生或用户设备所能获取到的后台错误信息，例如系统中所出现的各种运行错误等。具体地，用户设备可以将上述错误信息保存在例如日志或数据库中以用于确定所述待分析对象的用户体验信息。
在一个实施例中，当用户开始操作待分析对象时，用户设备开始生成操作记录；当用户结束操作所述待分析对象时，用户设备结束生成所述操作记录。
在一个实施例中，用户设备还可以向网络设备发送该用户的操作记录。具体地，用户设备可以通过与网络设备间的特定接口，或通过网络向网络设备发送上述操作记录。
图3示出根据本发明又一个方面的实施例的用于确定用户体验的装置的示意图。所述用于确定用户体验的装置包括用于获取用户操作待分析对象的操作记录的装置31，以下简称第一获取装置31；用于基于所述操作记录，确定所述用户操作所述待分析对象的操作特征的装置 32，以下简称第一操作特征确定装置32；以及用于基于所述操作特征，确定所述待分析对象的用户体验信息的装置33，以下简称第一确定装置33。
其中，本实施例的装置可以通过用户设备以及网络设备来实现。所述用户设备包括但不限于PC机、平板电脑、智能手机、PDA等。所述网络设备包括但不限于单个网络服务器、多个网络服务器组成的服务器组或基于云计算(Cloud Computing)的由大量计算机或网络服务器构成的云，其中，云计算是分布式计算的一种，由一群松散耦合的计算机集组成的一个超级虚拟计算机。
需要说明的是，所述用户设备仅为举例，其他现有的或今后可能出现的网络设备和用户设备如可适用于本发明，也应包含在本发明保护范围以内，并以引用方式包含于此。
首先，第一获取装置31将获取用户操作待分析对象的操作记录。
此处，待分析对象意指将分析其用户体验以得到其用户体验信息的对象。待分析对象可以为任意软件相关对象，例如软件界面、网页等。本领域技术人员应理解，上述对于待分析对象的描述仅为举例，任何适用于本发明原理的对象均以引用的方式包含于此。
此处，用户操作待分析对象的操作记录意指用户通过输入设备对待分析对象所进行的操作的记录。操作记录可以为例如用户通过输入设备来操作待分析对象时，该输入设备的轨迹记录，例如鼠标轨迹记录等。操作记录还可以为例如用户通过输入设备来操作待分析对象时，该输入设备的输入记录，例如鼠标点击输入记录、键盘输入记录等。此外，操作记录中还可以包括用户进行操作的时间信息，操作的具体位置信息等。此处，输入设备包括鼠标、键盘、触摸屏等任何类型的可用于输入的设备。
具体地，第一获取装置31可以通过读取文件系统、通过特定接口或通过网络等方式来获取用户操作待分析对象的操作记录。
接着，第一操作特征确定装置32将基于该操作记录，确定该用户操作该待分析对象的操作特征。
此处，操作特征可以包括以下至少任一项：
-所述用户点击所述待分析对象中的同一区域的点击次数；
-所述用户在所述待分析对象的同一输入区域内进行输入操作的输入次数；
-所述用户操作所述待分析对象的操作持续时间；
-所述用户操作所述待分析对象的轨迹与预定轨迹之间的轨迹偏差。
其中，区域意指待分析对象中的某特定位置范围。例如，当待分析对象为网页时，区域可以为该网页中的特定元素，例如只读文本框，则用户操作该待分析对象的操作特征可以为该用户点击该只读文本框的点击次数。
此处，输入区域意指能够供用户进行输入操作的区域。例如，当待分析对象为网页时，输入区域可以为该网页中的某输入文本框，则用户在该待分析对象的同一输入区域内进行输入操作的输入次数可以为该用户在该输入文本框中进行输入操作的输入次数。
此处，用户操作待分析对象的操作持续时间指用户在开始对该待分析对象进行操作至该用户结束对该分析对象的操作之间所持续的时间。
此处，用户操作该待分析对象的轨迹与该待分析对象的预定轨迹之间的轨迹偏差指轨迹之间的差距。轨迹可以由一系列坐标点或坐标点位置范围所构成。当用户对该待分析对象进行操作时，记录该用户各次操作的坐标点位置，则各次操作的坐标点位置形成了用户操作该待分析对象的轨迹。预定轨迹可以通过例如以较优方式来操作该待分析对象时，记录各次操作的坐标点位置或位置范围，则各次操作的坐标点位置或位置范围形成了该待分析对象的预定轨迹。可以通过将用户操作该待分析对象的轨迹中的各个坐标点按顺序与该待分析对象的预定轨迹中的各个坐标点进行比较来得出轨迹之间的差距。例如，当比对的两个坐标点位置相同或相近，或当比对的坐标点位置落在另一比对的坐标点位置范围内时，可认为差距较小。反之，则认为差距 较大。本领域技术人员应理解，此处，对于轨迹及轨迹偏差的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
具体地，第一操作特征确定装置32可以通过第一获取装置31所获取的操作记录中所包括的输入设备的轨迹记录和/或输入设备的输入记录来确定该用户操作该待分析对象的操作特征。
例如，第一操作特征确定装置32可以通过分析操作记录中所包括的输入设备的输入记录和/或轨迹记录，得到用户点击所述待分析对象中的同一区域的点击次数。第一操作特征确定装置32也可以通过分析操作记录中所包括的输入设备的输入记录和/或轨迹记录以得到用户在所述待分析对象的同一输入区域内进行输入操作的输入次数。第一操作特征确定装置32还可以通过分析操作记录中的时间信息以得到用户操作所述待分析对象的操作持续时间。或者第一操作特征确定装置32也可以通过分析操作记录中所包括的输入设备的输入记录和/或轨迹记录，来得到用户操作所述待分析对象的轨迹。第一操作特征确定装置32并将该轨迹与该待分析对象的预定轨迹按照上文所述的方法进行比对以得到两者之间的轨迹偏差。
本领域技术人员应理解，此处，对于第一操作特征确定装置32的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
接着，第一确定装置33可基于上述操作特征，确定待分析对象的用户体验信息。
在一个实施例中，第一确定装置33中所包括的用于基于所述点击次数，确定所述用户操作所述待分析对象的用户体验信息的装置，以下简称第二确定装置331(未示出)，可以基于用户点击待分析对象中的同一区域的点击次数来确定该待分析对象的用户体验信息。具体地，第二确定装置331可以将所述点击次数与预定阈值进行比较来确定该用户体验信息。例如，当所述点击次数超过预定阈值时，则待分析对象可能存在影响用户操作的潜在问题，则第二确定装置331可确定该 待分析对象的用户体验较差。而对于该待分析对象的各个区域，当用户点击该区域的点击次数均未超出预定阈值时，则第二确定装置331可认为该待分析对象用户体验正常。在一个实施例中，第二确定装置331对于该待分析对象的各个不同区域，还可以设定权值，并将用户点击各个区域的加权平均值与预定阈值进行如上比较以得到该待分析对象的用户体验信息。本领域技术人员应理解，此处，对于第二确定装置331的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
在另一个实施例中，第一确定装置33中所包括的用于基于所述输入次数，确定所述用户操作所述待分析对象的用户体验信息的装置，以下简称第三确定装置332(未示出)，可以基于用户在待分析对象的同一输入区域内进行输入操作的输入次数来确定该待分析对象的用户体验信息。具体地，第三确定装置332可以将所述输入次数与预定阈值进行比较来确定该用户体验信息。例如，当所述输入次数超过预定阈值时，则待分析对象可能存在影响用户操作的潜在问题，则第三确定装置332可确定该待分析对象的用户体验较差。而对于该待分析对象的各个输入区域，当用户在该输入区域进行的输入操作的输入次数均未超出预定阈值时，则第三确定装置332可认为该待分析对象用户体验正常。在一个实施例中，对于该待分析对象的各个不同的输入区域，第三确定装置332还可以设定权值，并将用户在各个输入区域进行输入操作的输入次数的加权平均值与预定阈值进行如上比较以得到该待分析对象的用户体验信息。本领域技术人员应理解，此处，对于第三确定装置332的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
在又一个实施例中，第一确定装置33中所包括的用于基于所述操作持续时间，确定所述用户操作所述待分析对象的用户体验信息的装置，以下简称第四确定装置333(未示出)，可以基于用户操作待分析对象的操作持续时间来确定所述用户操作所述待分析对象的用户体验 信息。具体地，第四确定装置333可以将所述操作持续时间与预定阈值进行比较来确定该用户体验信息。例如，当所述操作持续时间超过预定阈值时，则待分析对象可能存在影响用户操作的潜在问题，则第四确定装置333可确定该待分析对象的用户体验较差。而当所述操作持续时间未超出预定阈值时，则第四确定装置333可认为该待分析对象用户体验正常。本领域技术人员应理解，此处，对于第四确定装置333的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
在再一个实施例中，第一确定装置33中所包括的用于基于所述轨迹偏差，确定所述用户操作所述待分析对象的用户体验信息的装置，以下简称第五确定装置334(未示出)，可以基于用户操作待分析对象的轨迹与所述待分析对象的预定轨迹之间的轨迹偏差，来确定所述用户操作所述待分析对象的用户体验信息。具体地，第五确定装置334可以将所述轨迹偏差与预定阈值进行比较来确定该用户体验信息。例如，当所述轨迹偏差超过预定阈值时，则待分析对象可能存在影响用户操作的潜在问题，则第五确定装置334可确定该待分析对象的用户体验较差。而当所述轨迹偏差未超出预定阈值时，则第五确定装置334可认为该待分析对象用户体验正常。本领域技术人员应理解，此处，对于第五确定装置334的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
在一个优选实施例中，第一确定装置33中还包括用于基于所确定的各项用户体验信息，确定所述待分析对象的用户体验信息的装置，以下简称第六确定装置335(未示出)。第六确定装置335可以基于按照上文所述的方法所确定的各项用户体验信息，来确定该待分析对象的用户体验信息。例如，第一确定装置33按照上文所述的方法，基于用户点击待分析对象中的同一区域的点击次数，确定出该待分析对象的用户体验信息为良好；基于用户在待分析对象的同一输入区域内进行输入操作的输入次数，确定出该待分析对象的用户体验信息为极差；基于用户操作待分析对象的操作持续时间，确定出所述用户操作所述 待分析对象的用户体验信息为较差。则第六确定装置335基于上述各项用户体验信息的平均值，可得出该待分析对象的用户体验信息为较差。在一个优选实施例中，第六确定装置335还可以对各项用户体验信息进行加权，并通过各项用户体验信息的加权平均值来得出该待分析对象的用户体验信息。本领域技术人员应理解，此处，对于第六确定装置335的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
在一个实施例中，第一确定装置33中包括用于对于多个用户，基于其中所述点击次数超过第一阈值的用户的数量，确定所述待分析对象的用户体验信息的装置，以下简称第七确定装置336(未示出)。对于多个用户，第七确定装置336可以基于其中点击待分析对象中的同一区域的点击次数超过第一阈值的用户的数量，确定所述待分析对象的用户体验信息。例如，对于100个用户，其中点击待分析对象中的同一区域的点击次数超过第一阈值的用户的数量为30个，该数量超过预定阈值20。则第七确定装置336可认为该待分析对象存在影响用户操作的潜在问题，从而确定该待分析对象的用户体验信息为较差。反之，若该数量未超过预定阈值，则第七确定装置336可确定该待分析对象的用户体验信息为正常。
在另一个实施例中，第一确定装置33中包括用于对于多个用户，基于其中所述输入次数超过第二阈值的用户的数量，确定所述待分析对象的用户体验信息的装置，以下简称第八确定装置337(未示出)。对于多个用户，第八确定装置337可以基于中所述输入次数超过第二阈值的用户的数量，确定所述待分析对象的用户体验信息。例如，对于100个用户，其中在待分析对象中的同一输入区域内进行输入操作的输入次数超过第二阈值的用户的数量为60个，该数量远超过预定阈值10。则第八确定装置337可认为该待分析对象存在严重影响用户操作的潜在问题，从而确定该待分析对象的用户体验信息为极差。反之，若该数量未超过预定阈值，则第八确定装置337可确定该待分析对象的用户体验信息为良好。
在又一个实施例中，第一确定装置33中包括用于对于多个用户，基于其中所述操作持续时间超过第三阈值的用户的数量，确定所述待分析对象的用户体验信息的装置，以下简称第九确定装置338(未示出)。对于多个用户，第九确定装置338可以基于其中所述操作持续时间超过第三阈值的用户的数量，确定所述待分析对象的用户体验信息。例如，对于100个用户，其中操作持续时间超过第三阈值的用户的数量为5个，该数量低于预定阈值10。则第九确定装置338可认为该待分析对象不存在影响用户操作的潜在问题，从而确定该待分析对象的用户体验信息为正常。反之，若该数量超过预定阈值，则第九确定装置338可确定该待分析对象的用户体验信息为较差。
在再一个实施例中，第一确定装置33中包括用于对于多个用户，基于其中所述轨迹偏差超过第四阈值的用户的数量，确定所述待分析对象的用户体验信息的装置，以下简称第十确定装置339(未示出)。对于多个用户，第十确定装置339可以基于其中所述轨迹偏差超过第四阈值的用户的数量，确定所述待分析对象的用户体验信息。例如，对于100个用户，其中操作待分析对象的轨迹与该待分析对象的预定轨迹之间的偏差超过第四阈值的用户的数量为25个，该数量略超过预定阈值20。则第十确定装置339可认为该待分析对象可能存在影响用户操作的潜在问题，从而确定该待分析对象的用户体验信息为偏差。反之，若该数量未超过预定阈值，则第十确定装置339可确定该待分析对象的用户体验信息为正常。此外，在还一个实施例中，第一确定装置33中包括用于对于多个用户，基于其中各个用户之间的所述轨迹记录之间的差异，确定所述待分析对象的用户体验信息的装置，以下简称第十一确定装置3310(未示出)。对于多个用户，第十一确定装置3310可以基于其中各个用户之间的所述轨迹记录之间的差异，确定所述待分析对象的用户体验信息。例如，对于100个用户，第十一确定装置3310可以将各个用户操作该待分析对象的轨迹记录进行统计分析以得出其差异。当统计分析结果为用户轨迹之间的差异大于预定阈值时，则第十一确定装置3310可认为该待分析对象可能存在影响用户操作的因素，例如没 有为用户提供清晰的提示信息，从而使得用户按其个人经验来进行操作从而在不同用户之间的操作轨迹差异较大。则第十一确定装置3310可确定该待分析对象的用户体验信息为较差。
此外，在一个实施例中，第一确定装置33中包括用于对于多个用户，基于所确定的各项用户体验信息，确定所述待分析对象的用户体验信息的装置，以下简称第十二确定装置3311(未示出)。对于多个用户，第十二确定装置3311还可以基于所确定的各项用户体验信息，确定所述待分析对象的用户体验信息。例如，第十二确定装置3311可以对于上述各项用户体验信息求平均值，或进行加权平均以得出所述待分析对象的用户体验信息。
在一个实施例中，第一确定装置33中包括用于对于多个用户，基于各个用户各自的所述操作特征，确定各个用户操作所述待分析对象的各自的用户体验信息的装置，以下简称第十三确定装置3312(未示出)；以及用于基于各个用户操作所述待分析对象的各自的用户体验信息，确定所述待分析对象的用户体验信息的装置，以下简称第十四确定装置3313(未示出)。对于多个用户，第十三确定装置3312可以首先基于各个用户各自的操作特征，确定各个用户操作待分析对象的用户体验信息。然后，第十四确定装置3313基于各个用户操作待分析对象的用户体验信息，确定该待分析对象的用户体验信息。例如，对于100个用户，第十三确定装置3312可以按照上文所述的方法，获取该100个用户操作待分析对象的各自的操作特征。第十四确定装置3313可以按照上文所述的方法基于各自的操作特征，确定各个用户操作该待分析对象的用户体验信息。假定其结果为对于其中70个用户，其操作该待分析对象的用户体验信息为较差；对于其中20个用户，其结果为正常；对于其中10个用户，其结果为较好。则第十四确定装置3313可以将各个用户的用户体验信息求取平均值以得出该待分析对象的用户体验信息。例如，在上例结果中，该待分析对象的用户体验信息为较差。在一个实施例中，第十四确定装置3313还可以对用户分配权值，例如根据用户类型，或用户经验值等来分配不同的权值。第十四 确定装置3313并将各个用户的用户体验信息进行加权平均，以得出该待分析对象的用户体验信息。在另一个实施例中，第十四确定装置3313还可以将其用户体验信息低于某个阈值，例如用户体验信息较差的用户的数量与预定阈值进行比较。若超过预定阈值数量的用户均具有较差的用户体验信息，则第十四确定装置3313确定该待分析对象的用户体验信息为较差。本领域技术人员应理解，此处，对于第十四确定装置3313的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
在一个优选实施例中，第一获取装置11还包括用于获取所述用户操作所述待分析对象过程中所产生的一个或多个错误信息的装置，以下简称第二获取装置111(未示出)；第一确定装置11还包括用于基于所述操作特征，并结合所述一个或多个错误信息，确定所述待分析对象的用户体验信息的装置，以下简称第十五确定装置1114(未示出)。
第二获取装置111可以获取用户操作待分析对象的过程中所产生的一个或多个错误信息；并且，第十五确定装置1114(基于按照上文所述方法所得出的用户的操作特征，并结合该一个或多个错误信息，来确定该待分析对象的用户体验信息。具体地，第二获取装置111可以通过文件系统操作，或通过特定接口，或通过网络等方式来获取用户操作待分析对象的过程中所产生的一个或多个错误信息。其中，所述错误信息可以为前台错误信息，例如系统向用户给出的错误操作提示等。所述错误信息也可以为后台错误信息，例如系统中所出现的各种运行错误等。当第十五确定装置1114确定该待分析对象的用户体验信息时，可以结合考虑用户的操作特征与错误信息。例如，当基于用户的操作特征所确定的用户体验信息为正常，然而存在多个错误信息并且其中某个错误信息的错误等级为严重，则第十五确定装置1114仍可认为该待分析对象的用户体验信息较差。本领域技术人员应理解，此处，对于第十五确定装置1114的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
在一个实施例中，所述用于确定用户体验的装置还包括用于基于所述操作特征，并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息的装置，以下简称第一生成装置34(未示出)。
第一生成装置34可以基于用户的操作特征，并结合用户操作待分析对象的过程中所产生的一个或多个错误信息，生成该待分析对象的用户体验预警信息。例如，当按照上文所述的方法，基于用户的操作特征，并结合用户操作待分析对象的过程中所产生的一个或多个错误信息，确定出该待分析对象的用户体验信息为较差时，第一生成装置34可以生成该待分析对象的用户体验预警信息“预警：用户体验较差！”。
在一个实施例中，对于多个用户，第一生成装置34可以基于其中用户点击待分析对象的同一区域的点击次数超过第五阈值的用户的数量，或基于其中用户在待分析对象的同一输入区域内进行输入的输入次数超过第六阈值的用户的数量，或基于其中用户操作待分析对象的操作持续时间超过第七阈值的用户的数量，或基于其中用户操作待分析对象的轨迹与该待分析对象的预定轨迹之间的轨迹偏差超过第八阈值的用户的数量，或基于其中各个用户之间的所述轨迹记录之间的差异；并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息。例如，当所述点击次数超过第五阈值的用户数量较少，然而各个用户操作该待分析对象的过程中所产生的错误信息数量较多，并且存在严重错误，则第一生成装置34仍可确定该待分析对象的用户体验较差并生成该待分析对象的用户体验预警信息“预警：用户体验较差！”。
本领域技术人员应理解，此处，对于第一生成装置34的相关描述仅为示例性而非限定性描述，存在其他各种实现方式而不背离本发明的精神或范畴，并以引用的方式包含于此。
在一个实施例中，所述用于确定用户体验的装置还包括用于基于待分析对象的各个版本的用户体验信息，确定所述待分析对象的各个版本之间的用户体验差异信息的装置，以下简称差异确定装置35(未示出)。
差异确定装置35可以基于待分析对象的各个版本的用户体验信息，确定所述待分析对象的各个版本之间的用户体验差异信息。具体地，差异确定装置35可以将待分析对象的各个版本的用户体验信息进行比较，以确定其用户体验差异信息。通过该用户体验差异信息，差异确定装置35可以将具有较好用户体验的待分析对象的版本与其他版本进行比较，以得出其可能使得用户体验较优的区别之处。通过不同版本之间的用户体验差异信息的比较，可以有利于改进待分析对象以提高其用户体验。
本领域技术人员还应理解，上文所述的各个阈值仅为举例，并且各个阈值可以根据实际需要来动态调节。
图4示出根据本发明再一个方面的实施例的在用户设备端用于辅助确定用户体验的装置的示意图。其中，该装置包括用于根据用户对待分析对象的操作，生成操作记录，该操作记录用于确定所述待分析对象的用户体验信息的装置41，以下简称第一记录生成装置41。
第一记录生成装置41根据用户对待分析对象的操作，生成操作记录，该操作记录用于确定所述待分析对象的用户体验信息。
此处，待分析对象意指将分析其用户体验以得到其用户体验信息的对象。待分析对象可以为任意软件相关对象，例如软件界面、网页等。本领域技术人员应理解，上述对于待分析对象的描述仅为举例，任何适用于本发明原理的软件相关对象均以引用的方式包含于此。
此处，操作记录意指用户通过输入设备对待分析对象所进行的操作的记录。操作记录可以为例如用户通过输入设备来操作待分析对象时，该输入设备的轨迹记录，例如鼠标轨迹记录等。操作记录还可以为例如用户通过输入设备来操作待分析对象时，该输入设备的输入记录，例如鼠标点击输入记录、键盘输入记录等。此外，操作记录中还可以包括用户进行操作的时间信息，操作的具体位置信息等。此处，输入设备包括鼠标、键盘、触摸屏等任何类型的可用于输入的设备。
具体地，第一记录生成装置41可以根据用户对待分析对象的操作，生成操作记录，并将操作记录保存在例如日志或数据库中以用于确定该待分析对象的用户体验信息。
在一个实施例中，该在用户设备端用于辅助确定用户体验的装置还包括用于记录所述用户操作所述待分析对象过程中所产生的一个或多个错误信息以用于确定所述待分析对象的用户体验信息的装置，以下简称错误记录装置42(未示出)。错误记录装置42记录用户操作所述待分析对象过程中所产生的一个或多个错误信息以用于确定所述待分析对象的用户体验信息。其中，所述错误信息可以为前台错误信息，例如系统向用户给出的错误操作提示等。所述错误信息也可以为在用户设备中所产生或错误记录装置42所能获取到的后台错误信息，例如系统中所出现的各种运行错误等。具体地，错误记录装置42可以将上述错误信息保存在例如日志或数据库中以用于确定所述待分析对象的用户体验信息。
在一个实施例中，当用户开始操作待分析对象时，第一记录生成装置41开始生成操作记录；当用户结束操作所述待分析对象时，第一记录生成装置41结束生成所述操作记录。
在一个实施例中，该在用户设备端用于辅助确定用户体验的装置还包括用于向网络设备发送所述用户的所述操作记录的装置，以下简称发送装置43(未示出)。发送装置43可以向网络设备发送该用户的操作记录。具体地，发送装置43可以通过与网络设备间的特定接口，或通过网络向网络设备发送上述操作记录。
需要注意的是，本发明可在软件和/或软件与硬件的组合体中被实施，例如，本发明的各个装置可采用专用集成电路(ASIC)或任何其他类似硬件设备来实现。在一个实施例中，本发明的软件程序可以通过处理器执行以实现上文所述步骤或功能。同样地，本发明的软件程序(包括相关的数据结构)可以被存储到计算机可读记录介质中，例如，RAM存储器，磁或光驱动器或软磁盘及类似设备。另外，本发明的一些步骤或功能可采用硬件来实现，例如，作为与处理器配合从而执行各个步骤或功能的电路。
对于本领域技术人员而言，显然本发明不限于上述示范性实施例的细节，而且在不背离本发明的精神或基本特征的情况下，能够以其 他的具体形式实现本发明。因此，无论从哪一点来看，均应将实施例看作是示范性的，而且是非限制性的，本发明的范围由所附权利要求而不是上述说明限定，因此旨在将落在权利要求的等同要件的含义和范围内的所有变化涵括在本发明内。不应将权利要求中的任何附图标记视为限制所涉及的权利要求。此外，显然“包括”一词不排除其他单元或步骤，单数不排除复数。系统权利要求中陈述的多个单元或装置也可以由一个单元或装置通过软件或者硬件来实现。第一，第二等词语用来表示名称，而并不表示任何特定的顺序。
虽然前面特别示出并且描述了示例性实施例，但是本领域技术人员将会理解的是，在不背离条款书的精神和范围的情况下，在其形式和细节方面可以有所变化。这里所寻求的保护在所附条款书中做了阐述。在下列编号条款中规定了各个实施例的这些和其他方面：
1.一种用于确定用户体验的方法，其中，该方法包括：
-获取用户操作待分析对象的操作记录；
-基于所述操作记录，确定所述用户操作所述待分析对象的操作特征；
-基于所述操作特征，确定所述待分析对象的用户体验信息。
2.根据条款1所述的方法，其中，所述操作记录包括以下至少任一项：
-所述用户通过输入设备来操作待分析对象时，所述输入设备的轨迹记录；
-所述用户通过输入设备来操作待分析对象时，所述输入设备的输入记录。
3.根据条款2所述的方法，其中，所述操作特征包括以下至少任一项：
-所述用户点击所述待分析对象中的同一区域的点击次数；
-所述用户在所述待分析对象的同一输入区域内进行输入操作的输入次数；
-所述用户操作所述待分析对象的操作持续时间；
-所述用户操作所述待分析对象的轨迹与所述待分析对象的预定轨迹之间的轨迹偏差。
4.根据条款3所述的方法，其中，所述基于所述操作特征，确定所述待分析对象的用户体验信息的步骤包括以下至少任一项：
-基于所述点击次数，确定所述用户操作所述待分析对象的用户体验信息；
-基于所述输入次数，确定所述用户操作所述待分析对象的用户体验信息；
-基于所述操作持续时间，确定所述用户操作所述待分析对象的用户体验信息；
-基于所述轨迹偏差，确定所述用户操作所述待分析对象的用户体验信息；
其中，所述基于所述操作特征，确定所述待分析对象的用户体验信息的步骤还包括：
-基于所确定的各项用户体验信息，确定所述待分析对象的用户体验信息。
5.根据条款3或4所述的方法，其中，所述基于所述操作特征，确定所述待分析对象的用户体验信息的步骤包括以下至少任一项：
-对于多个用户，基于其中所述点击次数超过第一阈值的用户的数量，确定所述待分析对象的用户体验信息；
-对于多个用户，基于其中所述输入次数超过第二阈值的用户的数量，确定所述待分析对象的用户体验信息；
-对于多个用户，基于其中所述操作持续时间超过第三阈值的用户的数量，确定所述待分析对象的用户体验信息；
-对于多个用户，基于其中所述轨迹偏差超过第四阈值的用户的数量，确定所述待分析对象的用户体验信息；
-对于多个用户，基于其中各个用户之间的所述轨迹记录之间的差异，确定所述待分析对象的用户体验信息；
其中，所述基于所述操作特征，确定所述待分析对象的用户体验信 息的步骤还包括：
-对于多个用户，基于所确定的各项用户体验信息，确定所述待分析对象的用户体验信息。
6.根据条款3至5中任一项所述的方法，其中，所述基于所述操作特征，确定所述待分析对象的用户体验信息的步骤包括：
-对于多个用户，基于各个用户各自的所述操作特征，确定各个用户操作所述待分析对象的各自的用户体验信息；
-基于各个用户操作所述待分析对象的各自的用户体验信息，确定所述待分析对象的用户体验信息。
7.根据条款3至6中任一项所述的方法，其中，所述获取用户操作待分析对象的操作记录的步骤还包括：
-获取所述用户操作所述待分析对象过程中所产生的一个或多个错误信息；
其中，所述基于所述操作特征，确定所述待分析对象的用户体验信息的步骤还包括：
-基于所述操作特征，并结合所述一个或多个错误信息，确定所述待分析对象的用户体验信息。
8.根据条款7所述的方法，其中，所述方法还包括：
-基于所述操作特征，并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息。
9.根据条款8所述的方法，其中，所述基于所述操作特征，并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息的步骤包括以下至少任一项：
-对于多个用户，基于其中所述点击次数超过第五阈值的用户的数量，并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息；
-对于多个用户，基于其中所述输入次数超过第六阈值的用户的数量，并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息；
-对于多个用户，基于其中所述操作持续时间超过第七阈值的用户的数量，并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息；
-对于多个用户，基于其中所述轨迹偏差超过第八阈值的用户的数量，并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息；
-对于多个用户，基于其中各个用户之间的所述轨迹记录之间的差异，并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息。
10.根据条款1至9中任一项所述的方法，其中，该方法还包括：
-基于待分析对象的各个版本的用户体验信息，确定所述待分析对象的各个版本之间的用户体验差异信息。
11.一种在用户设备端用于辅助确定用户体验的方法，其中，该方法包括：
-根据用户对待分析对象的操作，生成操作记录，该操作记录用于确定所述待分析对象的用户体验信息。
12.根据条款11所述的方法，其中，所述根据用户对待分析对象的操作，生成操作记录的步骤还包括：
-记录所述用户操作所述待分析对象过程中所产生的一个或多个错误信息以用于确定所述待分析对象的用户体验信息。
13.根据条款11或12所述的方法，其中，所述操作记录包括以下至少任一项：
-用户通过输入设备来操作待分析对象时，所述输入设备的轨迹记录；
-用户通过输入设备来操作待分析对象时，所述输入设备的输入记录。
14.根据条款11至13中任一项所述的方法，其中，所述根据用户对待分析对象的操作，生成操作记录的步骤包括：
-当所述用户开始操作待分析对象时，开始生成操作记录；
-当所述用户结束操作所述待分析对象时，结束生成所述操作记录。
15.根据条款11至14中任一项所述的方法，其中，该方法还包括：
-向网络设备发送所述用户的所述操作记录。
16.一种用于确定用户体验的装置，其中，该装置包括：
-用于获取用户操作待分析对象的操作记录的装置；
-用于基于所述操作记录，确定所述用户操作所述待分析对象的操作特征的装置；
-用于基于所述操作特征，确定所述待分析对象的用户体验信息的装置。
17.根据条款16所述的装置，其中，所述操作记录包括以下至少任一项：
-所述用户通过输入设备来操作待分析对象时，所述输入设备的轨迹记录；
-所述用户通过输入设备来操作待分析对象时，所述输入设备的输入记录。
18.根据条款17所述的装置，其中，所述操作特征包括以下至少任一项：
-所述用户点击所述待分析对象中的同一区域的点击次数；
-所述用户在所述待分析对象的同一输入区域内进行输入操作的输入次数；
-所述用户操作所述待分析对象的操作持续时间；
-所述用户操作所述待分析对象的轨迹与所述待分析对象的预定轨迹之间的轨迹偏差。
19.根据条款18所述的装置，其中，所述用于基于所述操作特征，确定所述待分析对象的用户体验信息的装置包括以下至少任一项：
-用于基于所述点击次数，确定所述用户操作所述待分析对象的用户体验信息的装置；
-用于基于所述输入次数，确定所述用户操作所述待分析对象的用户体验信息的装置；
-用于基于所述操作持续时间，确定所述用户操作所述待分析对象的用户体验信息的装置；
-用于基于所述轨迹偏差，确定所述用户操作所述待分析对象的用户体验信息的装置；
其中，所述用于基于所述操作特征，确定所述待分析对象的用户体验信息的装置还包括：
-用于基于所确定的各项用户体验信息，确定所述待分析对象的用户体验信息的装置。
20.根据条款18或19所述的装置，其中，所述用于基于所述操作特征，确定所述待分析对象的用户体验信息的装置包括以下至少任一项：
-用于对于多个用户，基于其中所述点击次数超过第一阈值的用户的数量，确定所述待分析对象的用户体验信息的装置；
-用于对于多个用户，基于其中所述输入次数超过第二阈值的用户的数量，确定所述待分析对象的用户体验信息的装置；
-用于对于多个用户，基于其中所述操作持续时间超过第三阈值的用户的数量，确定所述待分析对象的用户体验信息的装置；
-用于对于多个用户，基于其中所述轨迹偏差超过第四阈值的用户的数量，确定所述待分析对象的用户体验信息的装置；
-用于对于多个用户，基于其中各个用户之间的所述轨迹记录之间的差异，确定所述待分析对象的用户体验信息的装置；
其中，所述用于基于所述操作特征，确定所述待分析对象的用户体验信息的装置还包括：
-用于对于多个用户，基于所确定的各项用户体验信息，确定所述待分析对象的用户体验信息的装置。
21.根据条款18至20中任一项所述的装置，其中，所述用于基于所述操作特征，确定所述待分析对象的用户体验信息的装置包括：
-用于对于多个用户，基于各个用户各自的所述操作特征，确定各个用户操作所述待分析对象的各自的用户体验信息的装置；
-用于基于各个用户操作所述待分析对象的各自的用户体验信息，确定所述待分析对象的用户体验信息的装置。
22.根据条款18至21中任一项所述的装置，其中，所述用于获取用户操作待分析对象的操作记录的装置还包括：
-用于获取所述用户操作所述待分析对象过程中所产生的一个或多个错误信息的装置；
其中，所述用于基于所述操作特征，确定所述待分析对象的用户体验信息的装置还包括：
-用于基于所述操作特征，并结合所述一个或多个错误信息，确定所述待分析对象的用户体验信息的装置。
23.根据条款22所述的装置，其中，所述装置还包括：
-用于基于所述操作特征，并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息的装置。
24.根据条款23所述的装置，其中，所述用于基于所述操作特征，并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息的装置用于以下至少任一项：
-对于多个用户，基于其中所述点击次数超过第五阈值的用户的数量，并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息；
-对于多个用户，基于其中所述输入次数超过第六阈值的用户的数量，并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息；
-对于多个用户，基于其中所述操作持续时间超过第七阈值的用户的数量，并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息；
-对于多个用户，基于其中所述轨迹偏差超过第八阈值的用户的数量，并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息；
-对于多个用户，基于其中各个用户之间的所述轨迹记录之间的差 异，并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息。
25.根据条款16至24中任一项所述的装置，其中，该装置还包括：
-用于基于待分析对象的各个版本的用户体验信息，确定所述待分析对象的各个版本之间的用户体验差异信息的装置。
26.一种在用户设备端用于辅助确定用户体验的装置，其中，该装置包括：
-用于根据用户对待分析对象的操作，生成操作记录，该操作记录用于确定所述待分析对象的用户体验信息的装置。
27.根据条款26所述的装置，其中，所述用于根据用户对待分析对象的操作，生成操作记录的装置还包括：
-用于记录所述用户操作所述待分析对象过程中所产生的一个或多个错误信息以用于确定所述待分析对象的用户体验信息的装置。
28.根据条款26或27所述的装置，其中，所述操作记录包括以下至少任一项：
-用户通过输入设备来操作待分析对象时，所述输入设备的轨迹记录；
-用户通过输入设备来操作待分析对象时，所述输入设备的输入记录。
29.根据条款26至28中任一项所述的装置，其中，所述用于根据用户对待分析对象的操作，生成操作记录的装置用于：
-当所述用户开始操作待分析对象时，开始生成操作记录；
-当所述用户结束操作所述待分析对象时，结束生成所述操作记录。
30.根据条款26至29中任一项所述的装置，其中，该装置还包括：
-用于向网络设备发送所述用户的所述操作记录的装置。

Claims (23)

  1. 一种用于确定用户体验的方法，其中，该方法包括：
    -获取用户操作待分析对象的操作记录；
    -基于所述操作记录，确定所述用户操作所述待分析对象的操作特征；
    -基于所述操作特征，确定所述待分析对象的用户体验信息。
  2. 根据权利要求1所述的方法，其中，所述操作记录包括以下至少任一项：
    -所述用户通过输入设备来操作待分析对象时，所述输入设备的轨迹记录；
    -所述用户通过输入设备来操作待分析对象时，所述输入设备的输入记录。
  3. 根据权利要求2所述的方法，其中，所述操作特征包括以下至少任一项：
    -所述用户点击所述待分析对象中的同一区域的点击次数；
    -所述用户在所述待分析对象的同一输入区域内进行输入操作的输入次数；
    -所述用户操作所述待分析对象的操作持续时间；
    -所述用户操作所述待分析对象的轨迹与所述待分析对象的预定轨迹之间的轨迹偏差。
  4. 根据权利要求3所述的方法，其中，所述基于所述操作特征，确定所述待分析对象的用户体验信息的步骤包括以下至少任一项：
    -基于所述点击次数，确定所述用户操作所述待分析对象的用户体验信息；
    -基于所述输入次数，确定所述用户操作所述待分析对象的用户体 验信息；
    -基于所述操作持续时间，确定所述用户操作所述待分析对象的用户体验信息；
    -基于所述轨迹偏差，确定所述用户操作所述待分析对象的用户体验信息；
    其中，所述基于所述操作特征，确定所述待分析对象的用户体验信息的步骤还包括：
    -基于所确定的各项用户体验信息，确定所述待分析对象的用户体验信息。
  5. 根据权利要求3或4所述的方法，其中，所述基于所述操作特征，确定所述待分析对象的用户体验信息的步骤包括以下至少任一项：
    -对于多个用户，基于其中所述点击次数超过第一阈值的用户的数量，确定所述待分析对象的用户体验信息；
    -对于多个用户，基于其中所述输入次数超过第二阈值的用户的数量，确定所述待分析对象的用户体验信息；
    -对于多个用户，基于其中所述操作持续时间超过第三阈值的用户的数量，确定所述待分析对象的用户体验信息；
    -对于多个用户，基于其中所述轨迹偏差超过第四阈值的用户的数量，确定所述待分析对象的用户体验信息；
    -对于多个用户，基于其中各个用户之间的所述轨迹记录之间的差异，确定所述待分析对象的用户体验信息；
    其中，所述基于所述操作特征，确定所述待分析对象的用户体验信息的步骤还包括：
    -对于多个用户，基于所确定的各项用户体验信息，确定所述待分析对象的用户体验信息。
  6. 根据权利要求3至5中任一项所述的方法，其中，所述基于所述操作特征，确定所述待分析对象的用户体验信息的步骤包括：
    -对于多个用户，基于各个用户各自的所述操作特征，确定各个用户操作所述待分析对象的各自的用户体验信息；
    -基于各个用户操作所述待分析对象的各自的用户体验信息，确定所述待分析对象的用户体验信息。
  7. 根据权利要求3至6中任一项所述的方法，其中，所述获取用户操作待分析对象的操作记录的步骤还包括：
    -获取所述用户操作所述待分析对象过程中所产生的一个或多个错误信息；
    其中，所述基于所述操作特征，确定所述待分析对象的用户体验信息的步骤还包括：
    -基于所述操作特征，并结合所述一个或多个错误信息，确定所述待分析对象的用户体验信息。
  8. 根据权利要求7所述的方法，其中，所述方法还包括：
    -基于所述操作特征，并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息。
  9. 一种在用户设备端用于辅助确定用户体验的方法，其中，该方法包括：
    -根据用户对待分析对象的操作，生成操作记录，该操作记录用于确定所述待分析对象的用户体验信息。
  10. 根据权利要求9所述的方法，其中，所述操作记录包括以下至少任一项：
    -用户通过输入设备来操作待分析对象时，所述输入设备的轨迹记录；
    -用户通过输入设备来操作待分析对象时，所述输入设备的输入记录。
  11. 一种用于确定用户体验的装置，其中，该装置包括：
    -用于获取用户操作待分析对象的操作记录的装置；
    -用于基于所述操作记录，确定所述用户操作所述待分析对象的操作特征的装置；
    -用于基于所述操作特征，确定所述待分析对象的用户体验信息的装置。
  12. 根据权利要求11所述的装置，其中，所述操作记录包括以下至少任一项：
    -所述用户通过输入设备来操作待分析对象时，所述输入设备的轨迹记录；
    -所述用户通过输入设备来操作待分析对象时，所述输入设备的输入记录。
  13. 根据权利要求12所述的装置，其中，所述操作特征包括以下至少任一项：
    -所述用户点击所述待分析对象中的同一区域的点击次数；
    -所述用户在所述待分析对象的同一输入区域内进行输入操作的输入次数；
    -所述用户操作所述待分析对象的操作持续时间；
    -所述用户操作所述待分析对象的轨迹与所述待分析对象的预定轨迹之间的轨迹偏差。
  14. 根据权利要求13所述的装置，其中，所述用于基于所述操作特征，确定所述待分析对象的用户体验信息的装置包括以下至少任一项：
    -用于基于所述点击次数，确定所述用户操作所述待分析对象的用户体验信息的装置；
    -用于基于所述输入次数，确定所述用户操作所述待分析对象的用 户体验信息的装置；
    -用于基于所述操作持续时间，确定所述用户操作所述待分析对象的用户体验信息的装置；
    -用于基于所述轨迹偏差，确定所述用户操作所述待分析对象的用户体验信息的装置；
    其中，所述用于基于所述操作特征，确定所述待分析对象的用户体验信息的装置还包括：
    -用于基于所确定的各项用户体验信息，确定所述待分析对象的用户体验信息的装置。
  15. 根据权利要求13或14所述的装置，其中，所述用于基于所述操作特征，确定所述待分析对象的用户体验信息的装置包括以下至少任一项：
    -用于对于多个用户，基于其中所述点击次数超过第一阈值的用户的数量，确定所述待分析对象的用户体验信息的装置；
    -用于对于多个用户，基于其中所述输入次数超过第二阈值的用户的数量，确定所述待分析对象的用户体验信息的装置；
    -用于对于多个用户，基于其中所述操作持续时间超过第三阈值的用户的数量，确定所述待分析对象的用户体验信息的装置；
    -用于对于多个用户，基于其中所述轨迹偏差超过第四阈值的用户的数量，确定所述待分析对象的用户体验信息的装置；
    -用于对于多个用户，基于其中各个用户之间的所述轨迹记录之间的差异，确定所述待分析对象的用户体验信息的装置；
    其中，所述用于基于所述操作特征，确定所述待分析对象的用户体验信息的装置还包括：
    -用于对于多个用户，基于所确定的各项用户体验信息，确定所述待分析对象的用户体验信息的装置。
  16. 根据权利要求13至15中任一项所述的装置，其中，所述用于 基于所述操作特征，确定所述待分析对象的用户体验信息的装置包括：
    -用于对于多个用户，基于各个用户各自的所述操作特征，确定各个用户操作所述待分析对象的各自的用户体验信息的装置；
    -用于基于各个用户操作所述待分析对象的各自的用户体验信息，确定所述待分析对象的用户体验信息的装置。
  17. 根据权利要求13至16中任一项所述的装置，其中，所述用于获取用户操作待分析对象的操作记录的装置还包括：
    -用于获取所述用户操作所述待分析对象过程中所产生的一个或多个错误信息的装置；
    其中，所述用于基于所述操作特征，确定所述待分析对象的用户体验信息的装置还包括：
    -用于基于所述操作特征，并结合所述一个或多个错误信息，确定所述待分析对象的用户体验信息的装置。
  18. 根据权利要求17所述的装置，其中，所述装置还包括：
    -用于基于所述操作特征，并结合所述一个或多个错误信息，生成所述待分析对象的用户体验预警信息的装置。
  19. 一种在用户设备端用于辅助确定用户体验的装置，其中，该装置包括：
    -用于根据用户对待分析对象的操作，生成操作记录，该操作记录用于确定所述待分析对象的用户体验信息的装置。
  20. 根据权利要求19所述的装置，其中，所述操作记录包括以下至少任一项：
    -用户通过输入设备来操作待分析对象时，所述输入设备的轨迹记录；
    -用户通过输入设备来操作待分析对象时，所述输入设备的输入记 录。
  21. 一种计算机可读存储介质，所述计算机可读存储介质包括计算机代码，当所述计算机代码被执行时，如权利要求1至10中任一项所述的方法被执行。
  22. 一种计算机程序产品，当所述计算机程序产品被计算机设备执行时，如权利要求1至10中任一项所述的方法被执行。
  23. 一种计算机设备，所述计算机设备包括存储器和处理器，所述存储器中存储有计算机代码，所述处理器被配置来通过执行所述计算机代码以执行如权利要求1至10中任一项所述的方法。
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