CN107315487B - Input processing method and device and electronic equipment - Google Patents
Input processing method and device and electronic equipment Download PDFInfo
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- CN107315487B CN107315487B CN201610270469.6A CN201610270469A CN107315487B CN 107315487 B CN107315487 B CN 107315487B CN 201610270469 A CN201610270469 A CN 201610270469A CN 107315487 B CN107315487 B CN 107315487B
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/02—Input arrangements using manually operated switches, e.g. using keyboards or dials
- G06F3/023—Arrangements for converting discrete items of information into a coded form, e.g. arrangements for interpreting keyboard generated codes as alphanumeric codes, operand codes or instruction codes
- G06F3/0233—Character input methods
- G06F3/0237—Character input methods using prediction or retrieval techniques
Abstract
The invention relates to the field of man-machine interaction, and discloses an input processing method, an input processing device and electronic equipment, which are used for solving the technical problem that a more accurate candidate item cannot be determined aiming at an input character string in the prior art. The method comprises the following steps: firstly, determining a first keyword set based on input content, and then acquiring parameter information corresponding to the first keyword set within a preset time range; and finally, determining a first keyword set recommendation candidate item based on the parameter information, namely providing a recommendation candidate item related to the input content by combining the real-time information of the keyword hit by the input content of the user, so that the recommendation candidate item more accurately hitting the user requirement can be determined, and the technical effect of improving the input efficiency is achieved.
Description
Technical Field
The invention relates to the field of human-computer interaction, in particular to an input processing method and device and electronic equipment.
Background
With the continuous development of scientific technology, electronic technology has also been developed rapidly, and the variety of electronic products is increasing. For example, electronic devices such as a notebook computer, a desktop computer, a smart phone, and a tablet computer have become an important part in life of people, and a user can use the electronic devices such as the mobile phone and the tablet computer to perform activities such as office work and entertainment anytime and anywhere, and enjoy convenience brought by scientific and technological development.
Electronic equipment in the prior art has a character input function, after a user starts an input method application program, a corresponding character string can be input by detecting input content of the user, and after the corresponding character string is input, some association candidate items can be provided based on the character string.
Disclosure of Invention
The invention provides an input processing method, an input processing device and electronic equipment, and aims to solve the technical problem that a more accurate candidate item cannot be determined aiming at an input character string in the prior art.
In a first aspect, an embodiment of the present invention provides an input processing method, including:
determining a first keyword set based on input content, the first keyword set comprising at least one keyword;
acquiring parameter information corresponding to the first keyword set within a preset time range;
and determining recommendation candidate items based on the parameter information.
Optionally, the obtaining of the parameter information corresponding to the first keyword set within the preset time range includes:
the parameter information is obtained by a different agent than the input method application.
Optionally, the obtaining the parameter information by another subject different from the input method application program includes:
determining a preset application program corresponding to the first keyword set, and querying through the preset application program to obtain the parameter information; and/or
Searching in a search engine through the first keyword set to obtain the parameter information; and/or
And acquiring the parameter information through a sensor corresponding to the first keyword set.
Optionally, the determining recommendation candidates based on the parameter information first keyword set includes:
determining a parameter range to which the parameter information belongs;
and acquiring the keyword corresponding to the parameter range from the corresponding relation between the parameter range and the keyword as the recommendation candidate item.
Optionally, the determining recommendation candidates based on the parameter information first keyword set includes:
acquiring at least one associated word corresponding to the first keyword set from the corresponding relation between the keywords and the associated words;
determining the recommendation priority of the at least one associated word based on the parameter value;
and taking the at least one associated word ranked according to the recommendation priority as the recommendation candidate item.
Optionally, the obtaining of the parameter information corresponding to the first keyword set within the preset time range includes:
acquiring target position information corresponding to the first keyword set;
and determining the parameter information corresponding to the target position information of the first keyword set.
Optionally, the obtaining of the target location information corresponding to the first keyword set includes:
extracting the target position information from the first keyword set; or
Determining user position information of a current electronic equipment user, wherein the user position information is the target position information; or
Judging whether the first keyword set contains the target position information or not; if the first keyword set contains the target position information, extracting the target position information from the first keyword set; and if the first keyword set does not contain the target position information, acquiring user position information of a user generating the input content as the target position information.
Optionally, the obtaining of the parameter information corresponding to the first keyword set within the preset time range includes: acquiring the parameter information corresponding to the first keyword set in a preset time period; alternatively, the first and second electrodes may be,
extracting the preset time range from the first keyword set; acquiring the parameter information corresponding to the first keyword set in the extracted time range; alternatively, the first and second electrodes may be,
judging whether the first keyword set contains the preset time range or not; if the first keyword set does not contain the preset time range, acquiring the parameter information corresponding to the first keyword set in a preset time period; if the first keyword set comprises the preset time range, extracting the preset time range from the first keyword set, and acquiring the parameter information corresponding to the first keyword set in the extracted time range.
In a second aspect, an embodiment of the present invention provides an input processing apparatus, including:
a first determining module, configured to determine a first keyword set based on input content, where the first keyword set includes at least one keyword;
the acquisition module is used for acquiring parameter information corresponding to the first keyword set within a preset time range;
and the second determining module is used for determining the recommendation candidate items based on the parameter information.
In a third aspect, an embodiment of the present invention provides an electronic device, including a memory, and one or more programs, where the one or more programs are stored in the memory, and configured to be executed by one or more processors includes instructions for:
determining a first keyword set based on input content, the first keyword set comprising at least one keyword;
acquiring parameter information corresponding to the first keyword set within a preset time range;
and determining recommendation candidate items based on the parameter information.
The invention has the following beneficial effects:
in the embodiment of the invention, a first keyword set is determined based on input content, and then parameter information corresponding to the first keyword set in a preset time range is acquired; and finally, determining a first keyword set recommendation candidate item based on the parameter information, namely providing a recommendation candidate item related to the input content by combining the real-time information of the keyword hit by the input content of the user, so that the recommendation candidate item more accurately hitting the user requirement can be determined, and the technical effect of improving the input efficiency is achieved.
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FIG. 1 is a flow chart of an input processing method according to an embodiment of the present invention;
FIG. 2 is a block diagram of an input processing device according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device implementing an input processing method according to an exemplary embodiment.
Detailed Description
The invention provides an input processing method, an input processing device and electronic equipment, and aims to solve the technical problem that accurate recommended candidate items cannot be determined for input contents of a user in the prior art.
In order to solve the technical problems, the general idea of the embodiment of the present application is as follows:
the method comprises the steps of firstly determining a first keyword set based on input content, wherein the first keyword set can be determined based on candidate items selected by a user and used as keywords contained in the first keyword set, the sum of the selected candidate items and keywords in a preset number before the selected candidate items can be used as the keywords contained in the first keyword set, the first keyword set can be determined based on context content of chatting between the user and friends, and the first keyword set can be determined based on the first N candidate items provided by an input method application program after characters are input by the user; then, parameter information corresponding to the first keyword set in a preset time range is obtained, and the preset time range can be obtained based on the first keyword set, for example, the first keyword set contains yesterday, and the preset time range is yesterday; if the first keyword set does not contain time-related information, a time range corresponding to today within a preset time range may be defaulted, for example, the preset time range may be obtained based on semantic analysis of input content of the user, for example: if the user input content is 'xxxx after work', the preset time range can be determined to be 18:00-21:00 of the current time, and if the input content is subjected to semantics, the preset time range cannot be analyzed, the preset time range can be determined to be within the preset time period of the current time; if "weather" is contained in the first keyword set, the parameter information is, for example: temperature information, pollution information, sky status, etc., and if the first keyword set contains "stock", the parameter information is, for example: large trend, volume, etc., and if the first keyword set contains "traffic", the parameter information is, for example: number limit information, congestion information, etc., and if the first keyword set contains "price of things", the parameter information is, for example: trend of price of things, etc.; and finally, determining a recommendation candidate item based on the parameter information, where the recommendation candidate item may be directly parameter information of the first keyword set, or may be obtained by processing the parameter information of the first keyword set, for example: if the first keyword set contains "weather" and the parameter information thereof is "temperature 30 ℃", the recommendation candidate may be "temperature 30 ℃", or "very hot", and the like, wherein a recommendation candidate may be determined jointly for a plurality of parameter information, for example: if the temperature is 30 ℃, it may be determined that the temperature is high, in which case, if it is cloudy, it may be determined that the recommended candidate word is stuffy; if the candidate words are good heat, insolation and the like, the candidate words can be recommended in sunny days, and more accurate recommendation candidate items can be determined based on a plurality of parameter information. That is, the recommendation candidate items related to the input content can be provided by combining the real-time information of the keywords hit by the input content of the user, so that the recommendation candidate items which hit the user requirements more accurately can be determined, and the technical effect of improving the input efficiency is achieved.
In addition, when determining the recommendation candidate, in addition to the real-time information of the keyword hit by the content that has been input by the user, the position information may be considered in combination, for example: acquiring user position information of a user generating input content, and acquiring parameter information corresponding to the user position information of a first keyword set; another example is: judging whether the first keyword set contains target position information or not, and if so, acquiring parameter information of the first keyword set at the target position; and if the target position information is not contained, acquiring parameter information of the first keyword set in the user position information and the like, thereby further improving the accuracy of generating the recommendation candidate.
In order to better understand the technical solutions of the present invention, the following detailed descriptions of the technical solutions of the present invention are provided with the accompanying drawings and the specific embodiments, and it should be understood that the specific features in the embodiments and the examples of the present invention are the detailed descriptions of the technical solutions of the present invention, and are not limitations of the technical solutions of the present invention, and the technical features in the embodiments and the examples of the present invention may be combined with each other without conflict.
In a first aspect, an embodiment of the present invention provides an input processing method, please refer to fig. 1, including:
step S101: determining a first keyword set based on the input content;
step S102: acquiring parameter information corresponding to the first keyword set within a preset time range;
step S103: and determining recommendation candidate items based on the parameter information.
For example, the scheme is applied to an electronic device with an input function, such as: a mobile phone, a tablet computer, a notebook computer, etc., embodiments of the present invention are not limited.
In step S101, the input content is, for example, input content received by an input method application, where the input content may be received by a physical keyboard, a virtual keyboard, a touch device, a tablet, a sound collection device, or the like. The input operation of the user to generate the input content may be various operations, such as: an operation of inputting a character string, an operation of selecting a candidate from a plurality of candidates, an operation of generating a preset gesture, and the like, which are not limited in the embodiments of the present invention. For example, if it is detected that the user selects a candidate from a plurality of candidates, in this case, a recommended candidate word may be further provided based on the candidate, so that the first keyword set may be determined based on the input content; or, when the preset gesture generated by the user is detected, it indicates that the user wants to provide the recommendation candidate item in the manner of the application, so that the first keyword set and the like can be determined based on the input content.
After detecting the input content, the first keyword set may be determined in a variety of ways, some of which are listed below for introduction.
First, a first keyword set is obtained based on the candidate selected by the user, for example: assuming that the user enters the following string "tianqi", several candidates may appear: weather, pseudo-ginseng, weather, and the candidate item weather are selected by the user through selection operation, so that two words of weather are input, and in this case, the candidate item (for example, weather) selected by the user can be used as a keyword contained in the first keyword set.
Determining search keywords based on the context content of the chat with the friend, for example, if the friend generates the following chat content of 'how much weather is today' for the user and the user continues to input 'today', determining that the user wants to input information related to 'weather' based on the context content, and thus determining that the keyword contained in the first keyword set is weather.
And determining the first keyword set based on the top N (for example, 1, 2 and the like) candidates provided by the input method application program after the user inputs the characters. For example: assuming that the user enters the following string "tianqi", several candidates may appear: weather, pseudo-ginseng, curiosity, weather of candidate item, can be directly used as a keyword contained in a first keyword set, and then a recommended candidate item corresponding to the weather of the candidate item, under the condition, input content can be displayed on the same screen with the recommended candidate item, and then a user can select a needed keyword to be displayed on the screen between the candidate item and the recommended candidate item, for example: suppose that a recommended candidate corresponding to weather candidate (i) includes: the method comprises the following steps of firstly, well heating, then, 30 ℃, simultaneously displaying candidate items, namely weather, Tianqi, and recommended candidate items, namely well heating, then, 30 ℃, further, if a user wants to input weather, the user can directly select to screen the recommended candidate items on the screen well and does not need to screen the candidate items on the weather, or when detecting that the user screens the recommended candidate items on the screen well, the candidate items (such as weather) for determining a first keyword set can be also screened, so that the final screened content is as follows: the weather is hot, thereby improving the input efficiency.
In addition to the candidate item on the screen of the user as a partial keyword included in the first keyword set, a preset number (e.g., 2, 4, 6, etc.) of keywords before the first keyword set are used as a part of the first keyword set, that is, the total of the candidate item on the screen and the preset number of keywords before the candidate item is used as the first keyword set, for example: before inputting "weather", the user further inputs "a point to go out to play and feel today", if the preset number is 2, the "today" and "weather" may be used together as the keywords included in the first keyword set, and of course, the first keyword set may also be determined in other ways, which is not limited in the embodiment of the present invention.
In a specific implementation process, when the first keyword set is obtained, it may be first determined whether the input content includes a preset keyword included in the preset keyword set, and if the input content includes the preset keyword, it is indicated that the first keyword set including the parameter information may be extracted based on the input content, and in this case, the first keyword set is extracted from the input content. The preset keyword set may be a pre-collected keyword set, for example: weather, traffic, stock market, movies, etc.; or, based on the input operation of the user, extracting a specific word and adding the specific word into a preset keyword set, for example: if the user is interested in the stock market based on the input operation of the user, the stock market can be added into a preset keyword set, for example: the 'movie' can be added to a preset keyword set and the like based on the input operation of the user to find that the user often inputs 'movie' related information.
In step S102, the preset time range may be determined in various ways, which are described below by way of example, and of course, the specific implementation process is not limited to the following cases.
Firstly, extracting a preset time range from a first keyword set, for example: assume that the first keyword set contains the following keywords: yesterday and weather, the preset time range can be determined as follows: yesterday.
By the scheme, the technical effect that the recommended candidate items can be determined based on the time information contained in the first keyword set is achieved.
② based on semantic analysis of the user input, for example, if the first keyword set contains the following keywords: after work and weather, the preset time range can be set as the time range corresponding to the current day by default, and semantic analysis is performed after work to determine that the time period corresponding to the current day is 18:00-21:00, so that the preset time range is 18:00-21:00 at the current day.
By the scheme, the technical effect that the recommendation candidate items can be determined based on the time information contained in the semantics of the voice input by the user is achieved.
And the default setting is to set the preset time range to be within the preset time period of the current time, for example: if the first keyword set does not contain the preset time range and the preset time range cannot be obtained through semantic analysis, it indicates that the user may need to know the current weather, and the preset time range may be set as: within 1 hour, within 30 minutes, etc.
By the scheme, the technical effect that the recommended candidate items can be determined based on the latest parameter information corresponding to the first keyword set is achieved.
Based on the difference of the first keyword sets, the parameter information corresponding to the first keyword sets is also different, and in general, the parameter information of the first keyword sets is determined by values or variation of the first keyword sets within a preset time range, for example: if the first keyword set contains "weather", the parameter information of the first keyword set is, for example: temperature information, pollution information, sky status, etc.; if the first keyword set contains "stock", the parameter information of the first keyword set is, for example: large trend, volume, etc., if the first keyword set contains "traffic", the parameter information of the first keyword set is, for example: limit number information, congestion information, etc. If the first keyword set contains "price of things", the parameter information of the first keyword set is, for example: trend of price of things, etc.
In step S102, the obtaining of the parameter information corresponding to the first keyword set within the preset time range includes: the parameter information is obtained by a different agent than the input method application.
For example, other subjects are, for example: hardware or other software, three of which are listed below for description, and certainly, the implementation process is not limited to the following three cases.
First, the obtaining the parameter information by another subject different from the input method application includes: and determining a preset application program corresponding to the first keyword set, and querying through the preset application program to obtain the parameter information.
For example, if the first keyword set contains "weather", a weather-related APP may be accessed through an input method application program, and then relevant weather information is obtained through query of the weather-related APP, for example: temperature information, pollution information, sky status, etc.; if the first keyword set contains "stock", stock-related APPs may be accessed through the input method application, and then related stock information may be obtained through stock-related APP queries, for example: large-dish strike, volume of volume, etc.; if the first keyword set contains traffic, the traffic-related APP can be accessed through an input method application program, and then the related traffic information is obtained through the query of the traffic-related APP, for example: limit number information, congestion information, etc.
Through the scheme, the technical effect that the parameter information corresponding to the APP related to the first keyword set can be provided through the APP related to the first keyword set is achieved, and therefore more accurate parameter information is obtained.
Secondly, the obtaining the parameter information by other subjects different from the input method application program comprises: and searching in a search engine through the first keyword set to obtain the parameter information.
For example, after obtaining the first keyword set, the first keyword set may be provided to a search engine, and then corresponding parameter information is obtained through search by the search engine, where when a search is performed by the search engine, there may be multiple search results for one keyword, so that the parameter information may be extracted from the first search result, or the parameter information may be extracted from an official authentication search result; or, the search results of the previous preset bars (e.g., 20, 30, etc.) are obtained, and then the search results are integrated to obtain the corresponding parameter information, etc.
By the scheme, the technical effect that reference can be provided for determining the recommendation candidate items of the first keyword set through the search result of the search engine is achieved.
Thirdly, the obtaining the parameter information through another subject different from the input method application program includes: and acquiring the parameter information through a sensor corresponding to the first keyword set.
For example, if the first keyword set contains "weather", temperature information can be acquired through a temperature sensor, an environment image is acquired through a camera, and then the environment image is analyzed to acquire a sky state; if the first keyword set contains traffic, an environment image can be acquired through camera acquisition, and then traffic jam information and the like can be acquired through analysis of the environment image.
By the scheme, the technical effect that reference can be provided for determining the recommendation candidate items of the first keyword set through the acquisition results of the sensors corresponding to the first keyword set is achieved.
In step S102, as an optional embodiment, when determining the parameter information of the first keyword set, in addition to the time parameter, the location parameter may be referred to, so as to determine more accurate parameter information, that is: the obtaining of the parameter information corresponding to the first keyword set within the preset time range includes: acquiring target position information corresponding to the first keyword set; and determining the parameter information corresponding to the position information of the first keyword set.
In the specific implementation process, the target position information may be determined in a variety of ways, and three of them are listed below for description, and of course, in the specific implementation process, the method is not limited to the following three cases.
The first step of obtaining the target location information corresponding to the first keyword set includes: and extracting the target position information from the first keyword set.
For example, assuming that the first keyword set is "beijing weather", the first keyword set includes target location information "beijing", so as to indicate that the user wishes to input information related to the weather of beijing, a recommended candidate item for "beijing weather" may be determined based on the weather information of beijing, of course, the determined target location information is different based on the difference of the first keyword set, and the embodiment of the present invention is not limited.
Secondly, the obtaining of the target location information corresponding to the first keyword set includes: and determining user position information of the current electronic equipment user, wherein the user position information is the target position information.
For example, the user location where the user is located may be obtained through detection of a positioning device carried by or externally connected to the current electronic device, and then parameter information of the first keyword set is obtained through the user location and a preset time range, for example: the user position is the achievement, the preset time range is yesterday, the first keyword set comprises weather, and then yesterday weather information can be obtained as parameter information of the first keyword set.
For another example, if the user position is a success ratio, and the first keyword set does not include the preset time range, the weather information within a preset time period (for example, within 1 hour) of the success ratio can be obtained as the parameter information of the first keyword set. Thirdly, the obtaining of the target location information corresponding to the first keyword set includes: judging whether the first keyword set contains the target position information or not; if the first keyword set contains the target position information, extracting the target position information from the first keyword set; and if the first keyword set does not contain the target position information, acquiring user position information of a user generating the input content as the target position information.
For example, assuming that the first keyword set is "beijing weather", the first keyword set includes target location information "beijing", so as to indicate that the user wishes to input information related to the weather of beijing, a recommended candidate item for "beijing weather" may be determined based on the weather information of beijing, if the first keyword set does not include time information, a recommended candidate item for "beijing weather" may be determined based on the weather information of beijing within a preset time period, and if the first keyword set includes time information, a recommended candidate item may be determined based on the weather information of beijing within a preset time range corresponding to the time information.
If the first keyword set does not contain the target position information, the fact that the user may want to input weather information of the current position (namely the user position) is indicated, so that the user position can be detected and obtained through the positioning equipment, and then candidate items aiming at the first keyword set are determined through the weather information of the user position; if the first keyword set does not contain time information, determining candidate items based on weather information of the user position in a preset time range; if the first keyword set contains time information, candidate items and the like can be determined based on weather information of the user position in a preset time range corresponding to the time information. Based on the scheme, the target position information can be accurately selected (for example, when the first keyword set contains the target position information, the target position information is directly extracted from the first keyword set, and when the keyword does not contain the target position information, the user position information is used as the target position information), so that the recommendation candidate item can be more accurately determined.
In step S103, the obtained parameter information may be directly used as a recommendation candidate for the first keyword set, for example, if the first keyword set includes "weather" and the obtained parameter information is "temperature 30 ℃", it may be determined that the recommendation candidate is temperature 30 ℃; for another example, if the first keyword set contains "stock", the obtained parameter information is "open now 2997.09", the recommended candidate may be determined to be "open now 2997.09", and so on.
Still alternatively, in step S103, recommendation candidates may be obtained based on processing the parameter information, and two ways of obtaining recommendation candidates by processing the parameter information are listed below, and of course, in a specific implementation process, the following two ways are not limited.
The first step of determining the recommended candidate items for the first keyword set in the character input process based on the parameter information includes: determining a parameter range to which the parameter value belongs; and acquiring the keyword corresponding to the parameter range as the recommended candidate item from the corresponding relation between the parameter range and the keyword, wherein the corresponding relation can be a corresponding relation preset by a system, and can also be a corresponding relation which is more in line with the expression habit of the user on the basis of the input habit of the user. For example: the system can preset the correspondence of 'temperature 30 ℃ to' very hot 'in the correspondence, and preset the correspondence of' temperature 10 ℃ to 'good cold' in the correspondence; for example, if the user a prefers to input "hot death" when the weather is hot, the user B prefers to say "hot cheer" when the weather is hot, the user B prefers to input "temperature 30 ° and" hot cheer "when the weather is hot, the user B prefers to input" frozen cheer "when the weather is cold, the user B prefers to input" temperature 10 ° and "frozen cheer" when the weather is cold, the user B prefers to input "winter sleep" when the weather is cold, and the user B prefers to input "temperature 10 ° and" winter sleep "when the weather is cold.
For example, assuming that the first keyword set includes "weather", the obtained parameter information is "temperature 30 ℃", and there is a correspondence between the parameter range and the keyword as shown in table 1:
TABLE 1
| Parameter Range (. degree. C.) | <10 | 10～28 | >28 |
| Keyword | Is lower than | Is moderate | Is higher than |
However, it may be determined by a temperature of 30 ℃ that the parameter range is >28, so that the corresponding recommended candidate may be determined to be higher, and after determining the recommended candidate for the first keyword set, a default candidate may also be provided for it, which is determined, for example, by the word frequency corresponding to the keyword.
The recommendation candidate words can be determined jointly according to a plurality of parameter information, for example: if the temperature is 30 ℃, it may be determined that the temperature is high, in which case, if it is cloudy, it may be determined that the recommended candidate word is stuffy; if the candidate words are good heat, insolation and the like, the candidate words can be recommended in sunny days, and more accurate recommendation candidate items can be determined based on a plurality of parameter information.
Secondly, the determining recommended candidate items for the first keyword set in the character input process based on the parameter information includes: acquiring at least one associated word corresponding to the first keyword set from the corresponding relation between the keywords and the associated words; determining the recommendation priority of the at least one associated word based on the parameter value; and taking the at least one associated word ranked according to the recommendation priority as the recommendation candidate item.
For example, assuming that the first keyword set contains "weather", the obtained parameter information is PM2.5(132), and the following associated words exist for the first keyword set "weather": good, light pollution and heavy pollution, and the default recommendation ranks of the three associated words are as follows: the method comprises the following steps of (1) good, (7) light pollution, (7) heavy pollution, wherein the pollution degree corresponding to PM2.5 is light pollution, so that the recommended priority of the light pollution is advanced, and the following recommended candidates, (i) light pollution, (ii) good, (ii) heavy pollution are obtained.
In a second aspect, based on the same inventive concept, an embodiment of the present invention provides an input processing apparatus, please refer to fig. 2, including:
a first determining module 20, configured to determine a first keyword set based on input content, where the first keyword set includes at least one keyword;
an obtaining module 21, configured to obtain parameter information corresponding to the first keyword set within a preset time range;
and a second determining module 22, configured to determine recommendation candidates based on the parameter information.
Optionally, the obtaining module 21 is configured to:
the parameter information is obtained by a different agent than the input method application.
Optionally, the obtaining module 21 is configured to:
determining a preset application program corresponding to the first keyword set, and querying through the preset application program to obtain the parameter information; and/or
Searching in a search engine through the first keyword set to obtain the parameter information; and/or
And acquiring the parameter information through a sensor corresponding to the first keyword set.
Optionally, the second determining module 22 includes:
the first determining unit is used for determining the parameter range to which the parameter information belongs;
and the first acquisition unit is used for acquiring the keyword corresponding to the parameter range from the corresponding relation between the parameter range and the keyword as the recommendation candidate item.
Optionally, the second determining module 22 includes:
the second obtaining unit is used for obtaining at least one associated word corresponding to the first keyword set from the corresponding relation between the keywords and the associated words;
the second determining unit is used for determining the recommendation priority of the at least one associated word based on the parameter value;
and the ranking unit is used for taking the at least one associated word ranked according to the recommendation priority as the recommendation candidate item.
Optionally, the obtaining module 21 includes:
a third obtaining unit, configured to obtain target location information corresponding to the first keyword set;
and a third determining unit, configured to determine the parameter information corresponding to the target location information of the first keyword set.
Optionally, the third obtaining unit is configured to:
extracting the target position information from the first keyword set; or
Determining user position information of a current electronic equipment user, wherein the user position information is the target position information; or
Judging whether the first keyword set contains the target position information or not; if the first keyword set contains the target position information, extracting the target position information from the first keyword set; and if the first keyword set does not contain the target position information, acquiring user position information of a user generating the input content as the target position information.
Optionally, the obtaining module 21 is configured to:
acquiring the parameter information corresponding to the first keyword set in a preset time period; alternatively, the first and second electrodes may be,
extracting the preset time range from the first keyword set; acquiring the parameter information corresponding to the first keyword set in the extracted time range; alternatively, the first and second electrodes may be,
judging whether the first keyword set contains the preset time range or not; if the first keyword set does not contain the preset time range, acquiring the parameter information corresponding to the first keyword set in a preset time period; if the first keyword set comprises the preset time range, extracting the preset time range from the first keyword set, and acquiring the parameter information corresponding to the first keyword set in the extracted time range.
Since the input processing apparatus described in the second aspect of the present invention is a device used for implementing the input processing method described in the first aspect of the present invention, based on the input processing method described in the first aspect of the present invention, a person skilled in the art can implement the specific structure and the modifications of the apparatus described in the second aspect of the present invention, and therefore details are not described herein again, and all the apparatuses used for implementing the input processing method described in the first aspect of the present invention belong to the scope of the present invention to be protected.
In a third aspect, based on the same inventive concept, an embodiment of the present invention provides an electronic device, including a memory, and one or more programs, where the one or more programs are stored in the memory, and configured to be executed by the one or more processors, and the one or more programs include instructions for:
determining a first keyword set based on input content, the first keyword set comprising at least one keyword;
acquiring parameter information corresponding to the first keyword set within a preset time range;
and determining recommendation candidate items based on the parameter information.
Since the electronic device described in the third aspect of the present invention is an electronic device used for implementing the input processing method described in the first aspect of the present invention, based on the input processing method described in the first aspect of the present invention, a person skilled in the art can implement the specific structure and the modifications of the electronic device described in the third aspect of the present invention, and therefore details are not described here, and all electronic devices used for implementing the input processing method described in the first aspect of the present invention belong to the scope of the present invention to be protected.
FIG. 3 is a block diagram illustrating an electronic device 800 for implementing an input processing method according to an example embodiment. For example, the electronic device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a gaming console, a tablet device, a medical device, a fitness device, a personal digital assistant, a mobile terminal, a wearable device, a vehicle-mounted device, and so forth.
Referring to fig. 3, electronic device 800 may include one or more of the following components: processing component 802, memory 804, power component 806, multimedia component 808, audio component 810, input/output (I/O) interface 812, sensor component 814, and communication component 816.
The processing component 802 generally controls overall operation of the electronic device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing components 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.
The memory 804 is configured to store various types of data to support operation at the device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
The power supply component 806 provides power to the various components of the electronic device 800. The power components 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.
The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the electronic device 800 is in an operation mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.
The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.
The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor assembly 814 includes one or more sensors for providing various aspects of state assessment for the electronic device 800. For example, the sensor assembly 814 may detect an open/closed state of the device 800, the relative positioning of components, such as a display and keypad of the electronic device 800, the sensor assembly 814 may also detect a change in the position of the electronic device 800 or a component of the electronic device 800, the presence or absence of user contact with the electronic device 800, orientation or acceleration/deceleration of the electronic device 800, and a change in the temperature of the electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast associated information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communications component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the electronic device 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.
In an exemplary embodiment, two non-transitory computer-readable storage media are also provided, such as the memory 804 including instructions executable by the processor 820 of the electronic device 800 to perform the above-described methods. For example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
A non-transitory computer readable storage medium in which instructions, when executed by a processor of an electronic device, enable the electronic device to perform a method of input processing, the method comprising:
determining a first keyword set based on input content, the first keyword set comprising at least one keyword;
acquiring parameter information corresponding to the first keyword set within a preset time range;
and determining recommendation candidate items based on the parameter information.
One or more embodiments of the invention have at least the following beneficial effects:
in the embodiment of the invention, a first keyword set is determined based on input content, and then parameter information corresponding to the first keyword set in a preset time range is acquired; and finally, determining recommended candidate items based on the parameter information, namely providing recommended candidate items related to the input content by combining with real-time information of keywords hit by the input content of the user, so that the recommended candidate items which hit the user requirements more accurately can be determined, and the technical effect of improving the input efficiency is achieved.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made in the embodiments of the present invention without departing from the spirit or scope of the embodiments of the invention. Thus, if such modifications and variations of the embodiments of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to encompass such modifications and variations.
Claims (14)
1. An input processing method, comprising:
determining a first keyword set based on input content, the first keyword set comprising at least one keyword;
acquiring parameter information corresponding to the first keyword set within a preset time range, wherein the parameter information comprises: obtaining the parameter information through other subjects different from the input method application program;
the obtaining the parameter information through another subject different from the input method application program includes: determining a preset application program corresponding to the first keyword set, and querying through the preset application program to obtain the parameter information; and/or searching in a search engine through the first keyword set to obtain the parameter information; and/or acquiring the parameter information through a sensor corresponding to the first keyword set;
and determining recommendation candidate items based on the parameter information.
2. The method of claim 1, wherein said determining recommendation candidates based on said parameter information comprises:
determining a parameter range to which the parameter information belongs;
and acquiring the keyword corresponding to the parameter range from the corresponding relation between the parameter range and the keyword as the recommendation candidate item.
3. The method of claim 1, wherein said determining recommendation candidates based on said parameter information comprises:
acquiring at least one associated word corresponding to the first keyword set from the corresponding relation between the keywords and the associated words;
determining the recommendation priority of the at least one associated word based on the parameter information;
and taking the at least one associated word ranked according to the recommendation priority as the recommendation candidate item.
4. The method according to any one of claims 1 to 3, wherein the obtaining of the parameter information corresponding to the first keyword set within the preset time range includes:
acquiring target position information corresponding to the first keyword set;
and determining the parameter information corresponding to the target position information of the first keyword set.
5. The method of claim 4, wherein the obtaining of the target location information corresponding to the first set of keywords comprises:
extracting the target position information from the first keyword set; or
Determining user position information of a current electronic equipment user, wherein the user position information is the target position information; or
Judging whether the first keyword set contains the target position information or not; if the first keyword set contains the target position information, extracting the target position information from the first keyword set; and if the first keyword set does not contain the target position information, acquiring user position information of a user generating the input content as the target position information.
6. The method according to any one of claims 1 to 3, wherein obtaining parameter information corresponding to the first keyword set within a preset time range includes: acquiring the parameter information corresponding to the first keyword set in a preset time period; alternatively, the first and second electrodes may be,
extracting the preset time range from the first keyword set; acquiring the parameter information corresponding to the first keyword set in the extracted time range; alternatively, the first and second electrodes may be,
judging whether the first keyword set contains the preset time range or not; if the first keyword set does not contain the preset time range, acquiring the parameter information corresponding to the first keyword set in a preset time period; if the first keyword set comprises the preset time range, extracting the preset time range from the first keyword set, and acquiring the parameter information corresponding to the first keyword set in the extracted time range.
7. An input processing apparatus, comprising:
a first determining module, configured to determine a first keyword set based on input content, where the first keyword set includes at least one keyword;
the acquisition module is used for acquiring parameter information corresponding to the first keyword set within a preset time range;
the second determining module is used for determining recommendation candidate items based on the parameter information;
the obtaining module is configured to: obtaining the parameter information through other subjects different from the input method application program; the method is specifically used for: determining a preset application program corresponding to the first keyword set, and querying through the preset application program to obtain the parameter information; and/or searching in a search engine through the first keyword set to obtain the parameter information; and/or acquiring the parameter information through a sensor corresponding to the first keyword set.
8. The apparatus of claim 7, wherein the second determining module comprises:
the first determining unit is used for determining the parameter range to which the parameter information belongs;
and the first acquisition unit is used for acquiring the keyword corresponding to the parameter range from the corresponding relation between the parameter range and the keyword as the recommendation candidate item.
9. The apparatus of claim 7, wherein the second determining module comprises:
the second obtaining unit is used for obtaining at least one associated word corresponding to the first keyword set from the corresponding relation between the keywords and the associated words;
a second determining unit, configured to determine, based on the parameter information, a recommendation priority of the at least one relevant word;
and the ranking unit is used for taking the at least one associated word ranked according to the recommendation priority as the recommendation candidate item.
10. The apparatus of any of claims 7-9, wherein the obtaining module comprises:
a third obtaining unit, configured to obtain target location information corresponding to the first keyword set;
and a third determining unit, configured to determine the parameter information corresponding to the target location information of the first keyword set.
11. The apparatus of claim 10, wherein the third obtaining unit is to:
extracting the target position information from the first keyword set; or
Determining user position information of a current electronic equipment user, wherein the user position information is the target position information; or
Judging whether the first keyword set contains the target position information or not; if the first keyword set contains the target position information, extracting the target position information from the first keyword set; and if the first keyword set does not contain the target position information, acquiring user position information of a user generating the input content as the target position information.
12. The apparatus of any one of claims 7-9, wherein the obtaining module is to:
acquiring the parameter information corresponding to the first keyword set in a preset time period; alternatively, the first and second electrodes may be,
extracting the preset time range from the first keyword set; acquiring the parameter information corresponding to the first keyword set in the extracted time range; alternatively, the first and second electrodes may be,
judging whether the first keyword set contains the preset time range or not; if the first keyword set does not contain the preset time range, acquiring the parameter information corresponding to the first keyword set in a preset time period; if the first keyword set comprises the preset time range, extracting the preset time range from the first keyword set, and acquiring the parameter information corresponding to the first keyword set in the extracted time range.
13. An electronic device comprising a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by one or more processors the one or more programs including instructions for:
determining a first keyword set based on input content, the first keyword set comprising at least one keyword;
acquiring parameter information corresponding to the first keyword set within a preset time range, wherein the parameter information comprises: obtaining the parameter information through other subjects different from the input method application program;
the obtaining the parameter information through another subject different from the input method application program includes: determining a preset application program corresponding to the first keyword set, and querying through the preset application program to obtain the parameter information; and/or searching in a search engine through the first keyword set to obtain the parameter information; and/or acquiring the parameter information through a sensor corresponding to the first keyword set;
and determining recommendation candidate items based on the parameter information.
14. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, is adapted to carry out the method steps of any of claims 1 to 6.
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| CN109976548B (en) * | 2017-12-28 | 2022-07-19 | 北京搜狗科技发展有限公司 | Input method and input device |
| CN110110207B (en) * | 2018-01-18 | 2023-11-03 | 北京搜狗科技发展有限公司 | Information recommendation method and device and electronic equipment |
| CN110413133A (en) * | 2018-04-27 | 2019-11-05 | 北京搜狗科技发展有限公司 | A kind of input method and device |
| CN110858382A (en) * | 2018-08-24 | 2020-03-03 | 北京搜狗科技发展有限公司 | Information processing method and device and information processing device |
| CN109582768B (en) * | 2018-11-23 | 2021-08-24 | 北京搜狗科技发展有限公司 | Text input method and device |
| CN111736752B (en) * | 2020-06-28 | 2022-04-08 | 北京搜狗科技发展有限公司 | Content recommendation method and device |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101398834A (en) * | 2007-09-29 | 2009-04-01 | 北京搜狗科技发展有限公司 | Processing method and device for input information and input method system |
| CN102426591A (en) * | 2011-10-31 | 2012-04-25 | 北京百度网讯科技有限公司 | Method and device for operating corpus used for inputting contents |
| CN104298429A (en) * | 2014-09-25 | 2015-01-21 | 北京搜狗科技发展有限公司 | Information presentation method based on input and input method system |
| CN104503994A (en) * | 2014-12-04 | 2015-04-08 | 百度在线网络技术（北京）有限公司 | Information recommendation method and device based on input method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8838453B2 (en) * | 2010-08-31 | 2014-09-16 | Red Hat, Inc. | Interactive input method |
-
2016
- 2016-04-27 CN CN201610270469.6A patent/CN107315487B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101398834A (en) * | 2007-09-29 | 2009-04-01 | 北京搜狗科技发展有限公司 | Processing method and device for input information and input method system |
| CN102426591A (en) * | 2011-10-31 | 2012-04-25 | 北京百度网讯科技有限公司 | Method and device for operating corpus used for inputting contents |
| CN104298429A (en) * | 2014-09-25 | 2015-01-21 | 北京搜狗科技发展有限公司 | Information presentation method based on input and input method system |
| CN104503994A (en) * | 2014-12-04 | 2015-04-08 | 百度在线网络技术（北京）有限公司 | Information recommendation method and device based on input method |
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