CN106487664B - Information recommendation method and device and mobile terminal - Google Patents
Information recommendation method and device and mobile terminal Download PDFInfo
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- CN106487664B CN106487664B CN201611123747.1A CN201611123747A CN106487664B CN 106487664 B CN106487664 B CN 106487664B CN 201611123747 A CN201611123747 A CN 201611123747A CN 106487664 B CN106487664 B CN 106487664B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72403—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
- H04L51/21—Monitoring or handling of messages
- H04L51/214—Monitoring or handling of messages using selective forwarding
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
- H04L51/52—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail for supporting social networking services
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Abstract
The invention provides an information recommendation method, an information recommendation device and a mobile terminal, wherein the method comprises the following steps: determining the activity type preferred by the user according to the use condition of each application program on the mobile terminal; acquiring activity information which is the same as the activity type preferred by the user from the Internet; screening out activity information matched with the daily life state of the user according to the acquired activity information and recommending the activity information; the daily living states of the user include: the user's leisure time. According to the method and the device, the user can push the activity information preferred by the user according to the use condition of each application program in the mobile terminal, so that the recommendation is more accurate, the daily life of the user is enriched, the user experience is improved, and the market competitiveness of a mobile terminal product is invisibly enhanced.
Description
Technical Field
The invention relates to the technical field of mobile terminals, in particular to an information recommendation method and device and a mobile terminal.
Background
In the prior art, an application program actively pushes information to a user under the permission of the user, usually in an information pushing mode, so that the time spent by the user in searching on a network can be reduced. Information push is a technology for reducing information overload by pushing information required by a user on the internet through a certain technical standard or protocol.
The existing information push strategy is generally based on the behavior of a user in a single specific application, such as information input or click operation, to push a specified activity, and cannot utilize the use condition of the user on each application program in a mobile terminal to obtain the personal preference of the user, so as to perform accurate push, and therefore, the user experience is not good.
Disclosure of Invention
The invention aims to provide an information recommendation method, an information recommendation device and a mobile terminal, which push activity information preferred by a user by utilizing the use condition of the user to each application program in the mobile terminal.
The technical scheme adopted by the invention is that the information recommendation method comprises the following steps:
determining the activity type preferred by the user according to the use condition of each application program on the mobile terminal;
acquiring activity information which is the same as the activity type preferred by the user from the Internet;
screening out activity information matched with the daily life state of the user according to the acquired activity information and recommending the activity information; the daily living states of the user include: the user's leisure time.
Further, the determining the activity type preferred by the user according to the use condition of each application program on the mobile terminal includes:
presetting a first corresponding relation between an application program and an activity type; determining the activity type preferred by the user according to the collected use frequency of each application program on the mobile terminal on the basis of the first corresponding relation; or determining the activity type preferred by the user according to the collected checking frequency of the activity information of the set activity type in each application program;
the activity type includes at least one of: shopping activities, sports activities, entertainment activities, tourism activities.
Further, the method further comprises:
presetting a second corresponding relation between the use frequency and the preference degree or checking the second corresponding relation between the use frequency and the preference degree;
and determining the preference degree of the user for the preferred activity type according to the second corresponding relation.
Further, the obtaining of the activity information from the internet, which is the same as the activity type preferred by the user, includes:
and acquiring activity information which is the same as the activity type preferred by the user from the Internet through a web crawler tool.
Further, the daily life state of the user also includes at least one of the following: the method comprises the following steps of (1) obtaining the current position of a user, the common trip route of the user, the preset trip route of the user and the number of family members of the user;
the obtaining mode of the common travel route of the user or the preset travel route of the user comprises the following steps:
obtaining route input information according to an application program related to traffic travel in the using process; alternatively, input information at a set frequent occurrence route information entry or a scheduled travel route entry is received.
Further, the screening and recommending activity information matched with the daily life state of the user according to the acquired activity information includes:
and when the types of the screened activity information matched with the daily life state of the user are more than two, sorting and recommending the screened activity information according to the preference degree of the user to each activity type preferred.
The invention also provides an information recommendation device, which comprises:
the first determining module is used for determining the activity type preferred by the user according to the use condition of each application program on the mobile terminal;
the acquisition module is used for acquiring activity information which is the same as the activity type favored by the user from the Internet;
the recommendation module is used for screening out activity information matched with the daily life state of the user according to the acquired activity information and recommending the activity information; the daily living states of the user include: the user's leisure time.
Further, the first determining module is configured to:
presetting a first corresponding relation between an application program and an activity type; determining the activity type preferred by the user according to the collected use frequency of each application program on the mobile terminal on the basis of the first corresponding relation; or determining the activity type preferred by the user according to the collected checking frequency of the activity information of the set activity type in each application program;
the activity type includes at least one of: shopping activities, sports activities, entertainment activities, tourism activities.
Further, the apparatus further includes:
the second determining module is used for presetting a second corresponding relation between the use frequency and the preference degree or checking the second corresponding relation between the use frequency and the preference degree; and determining the preference degree of the user for the preferred activity type according to the second corresponding relation.
Further, the obtaining module is configured to obtain activity information, which is the same as the activity type preferred by the user, from the internet through a web crawler tool.
Further, the daily life state of the user also includes at least one of the following: the method comprises the following steps of (1) obtaining the current position of a user, the common trip route of the user, the preset trip route of the user and the number of family members of the user;
the obtaining module is further configured to obtain a common travel route of the user or a predetermined travel route of the user in the following manner:
obtaining route input information according to an application program related to traffic travel in the using process; alternatively, input information at a set frequent occurrence route information entry or a scheduled travel route entry is received.
Further, the recommendation module is configured to:
and when the types of the screened activity information matched with the daily life state of the user are more than two, sorting and recommending the screened activity information according to the preference degree of the user to each activity type preferred.
The invention also provides a mobile terminal, comprising a processor and a memory storing executable instructions of the processor, wherein the instructions are executed by the processor to perform the following operations:
determining the activity type preferred by the user according to the use condition of each application program on the mobile terminal;
acquiring activity information which is the same as the activity type preferred by the user from the Internet;
screening out activity information matched with the daily life state of the user according to the acquired activity information and recommending the activity information; the daily living states of the user include: the user's leisure time.
Further, the daily life state of the user also includes at least one of the following: the method comprises the following steps of (1) obtaining the current position of a user, the common trip route of the user, the preset trip route of the user and the number of family members of the user;
the processor performs operations further comprising: acquiring a common travel route of the user or a preset travel route of the user in the following way:
obtaining route input information according to an application program related to traffic travel in the using process; alternatively, input information at a set frequent occurrence route information entry or a scheduled travel route entry is received.
By adopting the technical scheme, the invention at least has the following advantages:
according to the information recommendation method, the information recommendation device and the mobile terminal, information such as activity types preferred by the user is obtained according to the use condition of the user to each application program in the mobile terminal, and activities preferred by the user and matched with the daily life state information of the user are obtained from the Internet and are recommended to the user.
Drawings
FIG. 1 is a flowchart of a method for recommending information according to a first embodiment of the present invention;
FIG. 2 is a flowchart of a method for recommending information according to a second embodiment of the present invention;
FIG. 3 is a flowchart of a method for recommending information according to a third embodiment of the present invention;
FIG. 4 is a schematic diagram of the structure of an information recommendation apparatus according to the fourth and fifth embodiments of the present invention;
FIG. 5 is a schematic diagram of an information recommendation apparatus according to a sixth embodiment of the present invention;
fig. 6 is a schematic composition diagram of a mobile terminal according to a seventh embodiment of the present invention;
fig. 7 is a flowchart illustrating an information recommendation method according to an eighth embodiment of the present invention.
Detailed Description
To further explain the technical means and effects of the present invention adopted to achieve the intended purpose, the present invention will be described in detail with reference to the accompanying drawings and preferred embodiments.
A first embodiment of the present invention, a method for recommending information, as shown in fig. 1, includes the following specific steps:
and step S101, determining the activity type preferred by the user according to the use condition of each application program on the mobile terminal.
Optionally, step S101 includes:
presetting a first corresponding relation between an application program and an activity type; and determining the activity type preferred by the user according to the collected use frequency of each application program on the mobile terminal on the basis of the first corresponding relation. Such as: and if the collected use frequency of any application program on the mobile terminal is greater than the set frequency threshold, determining the activity type corresponding to the application program as the activity type preferred by the user.
The activity type includes at least one of: shopping activities, sports activities, entertainment activities, tourism activities.
In step S102, activity information that is the same as the activity type preferred by the user is acquired from the internet.
Alternatively, step S102 may obtain the same activity information as the activity type preferred by the user from the internet through a tool such as a web crawler. Such as: the method comprises the steps of firstly acquiring activity information of various activity types from the Internet by using tools such as a web crawler and the like, and then filtering based on the activity types preferred by users to obtain the activity information which is the same as the activity types preferred by the users.
Step S103, screening out activity information matched with the daily life state of the user according to the acquired activity information and recommending the activity information; the daily living states of the user include: the user's leisure time.
Optionally, the user's leisure time includes: the user's own scheduled vacation time, and/or the national legal vacation.
Optionally, the activity information at least includes content of the activity and time information of the activity occurrence. The activity information acquired in step S102 may be expired activity information or activity information whose occurrence time conflicts with the leisure time of the user, and the activity information does not match with the daily life state of the user, and needs to be filtered out without recommendation, and the rest of the activity information matching with the daily life state of the user may be recommended.
The method of the embodiment classifies the application programs based on the activity types, determines the activity types preferred by the user according to the use conditions of the application programs on the mobile terminal, acquires the activity information which is the same as the activity types preferred by the user from the Internet, recommends the activity information effective for the user to the user according to the leisure time of the user, and can truly reflect the daily needs of the user on various types of activities because the activity types preferred by the user are counted by the application programs in the mobile terminal used by the user daily, thereby realizing accurate positioning on the preferences of the user.
A second embodiment of the present invention, a method for recommending information, as shown in fig. 2, includes the following specific steps:
step S201, determining the activity type preferred by the user according to the use condition of each application program on the mobile terminal.
Optionally, step S201 includes:
and determining the activity type preferred by the user according to the viewing frequency of the activity information of the set activity type in each collected application program. Such as: and if the viewing frequency of the activity information of the set activity type in each application program is greater than the set frequency threshold, determining the set activity type as the activity type preferred by the user.
The activity type includes at least one of: shopping activities, sports activities, entertainment activities, tourism activities.
In step S202, activity information that is the same as the activity type preferred by the user is acquired from the internet.
Alternatively, step S202 may obtain the same activity information as the activity type preferred by the user from the internet through a tool such as a web crawler. Such as: the method comprises the steps of firstly acquiring activity information of various activity types from the Internet by using tools such as a web crawler and the like, and then filtering based on the activity types preferred by users to obtain the activity information which is the same as the activity types preferred by the users.
Step S203, screening out activity information matched with the daily life state of the user according to the acquired activity information and recommending the activity information; the daily living states of the user include: a user's leisure time, and at least one of: the method comprises the following steps of (1) obtaining the current position of a user, the common trip route of the user, the preset trip route of the user and the number of family members of the user;
optionally, the user's leisure time includes: the user's own scheduled vacation time, and/or the national legal vacation.
Optionally, the obtaining method of the common travel route of the user or the predetermined travel route of the user includes:
obtaining route input information according to an application program related to traffic travel in the using process; alternatively, input information at a set frequent occurrence route information entry or a scheduled travel route entry is received.
The method for acquiring the number of family members of the user comprises the following steps: input information at the set family number information entry is received. The family number information of the user can be used for recommending a proper travel package to the user according to the family number of the user under the condition that the user likes travel activities, so that the recommendation is more accurate, and the recommendation effect is better.
Optionally, the activity information at least includes content of the activity and time information and location information of the activity. The activity information acquired in step S202 may be expired activity information or activity information whose occurrence time conflicts with the leisure time of the user, and the activity information does not match with the daily life state of the user and needs to be filtered out, and if the occurrence location in the remaining activity information coincides with the current location of the user, the frequent trip route of the user, or the predetermined trip route of the user, or is located near the current location of the user, the frequent trip route of the user, or the predetermined trip route of the user, the activity information may be considered as activity information matching with the daily life state of the user and may be recommended. The embodiment refers to more factors of places than the first embodiment, so the recommendation effect is better, and the activity type preferred by the user is counted by the application program in the mobile terminal used by the user daily, so that the daily needs of the user for various types of activities can be truly reflected, and the preference of the user is accurately positioned.
A third embodiment of the present invention provides a method for recommending information, as shown in fig. 3, including the following steps:
step S301, determining the activity type and the preference degree preferred by the user according to the use condition of each application program on the mobile terminal.
Optionally, step S301 includes:
presetting a first corresponding relation between an application program and an activity type; and determining the activity type preferred by the user according to the collected use frequency of each application program on the mobile terminal on the basis of the first corresponding relation. Such as: and if the collected use frequency of any application program on the mobile terminal is greater than the set frequency threshold, determining the activity type corresponding to the application program as the activity type preferred by the user.
Or determining the activity type preferred by the user according to the viewing frequency of the activity information of the set activity type in each collected application program. Such as: and if the viewing frequency of the activity information of the set activity type in each application program is greater than the set frequency threshold, determining the set activity type as the activity type preferred by the user.
The activity type includes at least one of: shopping activities, sports activities, entertainment activities, tourism activities.
Optionally, step S301 further includes:
presetting a second corresponding relation between the use frequency and the preference degree or checking the second corresponding relation between the use frequency and the preference degree;
and determining the preference degree of the user for the preferred activity type according to the second corresponding relation.
In step S302, activity information that is the same as the activity type preferred by the user is acquired from the internet.
Alternatively, step S302 may obtain the same activity information as the activity type preferred by the user from the internet through a tool such as a web crawler. Such as: the method comprises the steps of firstly acquiring activity information of various activity types from the Internet by using tools such as a web crawler and the like, and then filtering based on the activity types preferred by users to obtain the activity information which is the same as the activity types preferred by the users.
Step S303, when the types of the screened activity information matched with the daily life state of the user are more than two, sorting and recommending the screened activity information according to the preference degree of the user to each activity type preferred; the daily living states of the user include: a user's leisure time, and at least one of: the current position of the user, the common travel route of the user, the scheduled travel route of the user, and the number of family members of the user.
Optionally, the user's leisure time includes: the user's own scheduled vacation time, and/or the national legal vacation.
Optionally, the obtaining method of the common travel route of the user or the predetermined travel route of the user includes:
obtaining route input information according to an application program related to traffic travel in the using process; alternatively, input information at a set frequent occurrence route information entry or a scheduled travel route entry is received.
The method for acquiring the number of family members of the user comprises the following steps: input information at the set family number information entry is received. The family number information of the user can be used for recommending a proper travel package to the user according to the family number of the user under the condition that the user likes travel activities, so that the recommendation is more accurate, and the recommendation effect is better.
Optionally, the activity information at least includes content of the activity and time information and location information of the activity. The activity information acquired in step S302 may be expired activity information or activity information whose occurrence time conflicts with the leisure time of the user, and the activity information does not match with the daily life state of the user and needs to be filtered out, and if the occurrence location in the remaining activity information coincides with the current location of the user, the frequent trip route of the user, or the predetermined trip route of the user, or is located near the current location of the user, the frequent trip route of the user, or the predetermined trip route of the user, the activity information may be considered as activity information matching with the daily life state of the user and may be recommended.
The embodiment refers to more factors of places than the first embodiment, so the recommendation effect is better, and the activity type preferred by the user is counted by the application program in the mobile terminal used by the user daily, so that the daily needs of the user for various types of activities can be truly reflected, and the preference of the user is accurately positioned.
Compared with the second embodiment, the embodiment considers that the user may generate the preference for a plurality of types of activities, increases the statistics of the preference of the user for the preferred activity types, and can sort the activities preferred by the different types of users according to the preference and recommend the activities to the user when recommending the activities preferred by the different types of users to the user, thereby further improving the use experience of the user.
A fourth embodiment of the present invention, which corresponds to the first embodiment, introduces an information recommendation apparatus, as shown in fig. 4, including the following components:
1) the first determining module 401 is configured to determine a preferred activity type of the user according to a usage status of each application program on the mobile terminal.
Optionally, the first determining module 401 is configured to:
presetting a first corresponding relation between an application program and an activity type; and determining the activity type preferred by the user according to the collected use frequency of each application program on the mobile terminal on the basis of the first corresponding relation. Such as: and if the collected use frequency of any application program on the mobile terminal is greater than the set frequency threshold, determining the activity type corresponding to the application program as the activity type preferred by the user.
The activity type includes at least one of: shopping activities, sports activities, entertainment activities, tourism activities.
2) An obtaining module 402, configured to obtain activity information from the internet, the activity information being the same as the activity type preferred by the user.
Optionally, the obtaining module 402 is configured to obtain activity information, which is the same as the activity type preferred by the user, from the internet through a web crawler tool. Such as: the method comprises the steps of firstly acquiring activity information of various activity types from the Internet by using tools such as a web crawler and the like, and then filtering based on the activity types preferred by users to obtain the activity information which is the same as the activity types preferred by the users.
3) The recommending module 403 is configured to screen out and recommend activity information that matches with the daily life state of the user according to the acquired activity information; the daily living states of the user include: the user's leisure time.
Optionally, the user's leisure time includes: the user's own scheduled vacation time, and/or the national legal vacation.
Optionally, the activity information at least includes content of the activity and time information of the activity occurrence. The activity information acquired by the acquisition module 402 may be expired activity information or activity information whose occurring time conflicts with the leisure time of the user, and the activity information is not matched with the daily life state of the user, and needs to be filtered out without recommendation, and the rest of the activity information matched with the daily life state of the user can be recommended.
The device of the embodiment classifies the application programs based on the activity types, determines the activity types preferred by the user according to the use conditions of the application programs on the mobile terminal, acquires the activity information which is the same as the activity types preferred by the user from the Internet, and recommends the activity information which is effective for the user to the user according to the leisure time of the user.
A fifth embodiment of the present invention, which corresponds to the second embodiment, introduces an information recommendation apparatus, as shown in fig. 4, including the following components:
1) the first determining module 401 is configured to determine a preferred activity type of the user according to a usage status of each application program on the mobile terminal.
Optionally, the first determining module 401 is configured to:
and determining the activity type preferred by the user according to the viewing frequency of the activity information of the set activity type in each collected application program. Such as: and if the viewing frequency of the activity information of the set activity type in each application program is greater than the set frequency threshold, determining the set activity type as the activity type preferred by the user.
The activity type includes at least one of: shopping activities, sports activities, entertainment activities, tourism activities.
2) An obtaining module 402, configured to obtain activity information from the internet, the activity information being the same as the activity type preferred by the user.
Optionally, the obtaining module 402 is configured to obtain activity information, which is the same as the activity type preferred by the user, from the internet through a web crawler tool. Such as: the method comprises the steps of firstly acquiring activity information of various activity types from the Internet by using tools such as a web crawler and the like, and then filtering based on the activity types preferred by users to obtain the activity information which is the same as the activity types preferred by the users.
3) The recommending module 403 is configured to screen out and recommend activity information that matches with the daily life state of the user according to the acquired activity information; the daily living states of the user include: a user's leisure time, and at least one of: the method comprises the following steps of (1) obtaining the current position of a user, the common trip route of the user, the preset trip route of the user and the number of family members of the user;
optionally, the user's leisure time includes: the user's own scheduled vacation time, and/or the national legal vacation.
Optionally, the obtaining module 402 is further configured to: obtaining a common travel route of the user or a preset travel route of the user by the following method:
obtaining route input information according to an application program related to traffic travel in the using process; alternatively, input information at a set frequent occurrence route information entry or a scheduled travel route entry is received.
Optionally, the obtaining module 402 is further configured to: acquiring the number of family members of the user by the following method: input information at the set family number information entry is received. The family number information of the user can be used for recommending a proper travel package to the user according to the family number of the user under the condition that the user likes travel activities, so that the recommendation is more accurate, and the recommendation effect is better.
Optionally, the activity information at least includes content of the activity and time information and location information of the activity. The activity information acquired by the acquiring module 402 may be expired activity information or activity information whose occurring time conflicts with the leisure time of the user, the activity information is not matched with the daily life state of the user and needs to be filtered out, and if the occurring location in the remaining activity information coincides with the current location of the user, the common trip route of the user or the predetermined trip route of the user, or is located near the current location of the user, the common trip route of the user or the predetermined trip route of the user, the activity information may be considered as activity information matched with the daily life state of the user and may be recommended. The embodiment refers to more factors of places than the first embodiment, so the recommendation effect is better, and the activity type preferred by the user is counted by the application program in the mobile terminal used by the user daily, so that the daily needs of the user for various types of activities can be truly reflected, and the preference of the user is accurately positioned.
A sixth embodiment of the present invention, which corresponds to the third embodiment, introduces an information recommendation apparatus, as shown in fig. 5, including the following components:
1) the first determining module 501 is configured to determine a preferred activity type of the user according to usage of each application program on the mobile terminal.
Optionally, the first determining module 501 is configured to:
presetting a first corresponding relation between an application program and an activity type; and determining the activity type preferred by the user according to the collected use frequency of each application program on the mobile terminal on the basis of the first corresponding relation. Such as: and if the collected use frequency of any application program on the mobile terminal is greater than the set frequency threshold, determining the activity type corresponding to the application program as the activity type preferred by the user.
Or determining the activity type preferred by the user according to the viewing frequency of the activity information of the set activity type in each collected application program. Such as: and if the viewing frequency of the activity information of the set activity type in each application program is greater than the set frequency threshold, determining the set activity type as the activity type preferred by the user.
The activity type includes at least one of: shopping activities, sports activities, entertainment activities, tourism activities.
2) A second determining module 502, configured to preset a second corresponding relationship between the usage frequency and the preference degree or check the second corresponding relationship between the usage frequency and the preference degree; and determining the preference degree of the user for the preferred activity type according to the second corresponding relation.
3) An obtaining module 503, configured to obtain activity information from the internet, where the activity information is the same as the activity type preferred by the user.
Optionally, the obtaining module 503 is configured to obtain activity information, which is the same as the activity type preferred by the user, from the internet through a web crawler tool. Such as: the method comprises the steps of firstly acquiring activity information of various activity types from the Internet by using tools such as a web crawler and the like, and then filtering based on the activity types preferred by users to obtain the activity information which is the same as the activity types preferred by the users.
4) The recommending module 504 is configured to, when the types of the screened activity information matched with the daily life state of the user are more than two, recommend the screened activity information after sorting according to the preference of the user to each activity type preferred; the daily living states of the user include: a user's leisure time, and at least one of: the method comprises the following steps of (1) obtaining the current position of a user, the common trip route of the user, the preset trip route of the user and the number of family members of the user;
optionally, the user's leisure time includes: the user's own scheduled vacation time, and/or the national legal vacation.
Optionally, the obtaining module 503 is further configured to: obtaining a common travel route of the user or a preset travel route of the user by the following method:
obtaining route input information according to an application program related to traffic travel in the using process; alternatively, input information at a set frequent occurrence route information entry or a scheduled travel route entry is received.
Optionally, the obtaining module 503 is further configured to: acquiring the number of family members of the user by the following method: input information at the set family number information entry is received. The family number information of the user can be used for recommending a proper travel package to the user according to the family number of the user under the condition that the user likes travel activities, so that the recommendation is more accurate, and the recommendation effect is better.
Optionally, the activity information at least includes content of the activity and time information and location information of the activity. The activity information acquired by the acquiring module 503 may be expired activity information or activity information whose occurrence time conflicts with the leisure time of the user, and the activity information is not matched with the daily life state of the user and needs to be filtered out, and if the occurrence location in the remaining activity information coincides with the current location of the user, the common trip route of the user, or the predetermined trip route of the user, or is located near the current location of the user, the common trip route of the user, or the predetermined trip route of the user, the activity information may be considered as activity information matched with the daily life state of the user and may be recommended.
The embodiment refers to more factors of places than the fourth embodiment, so the recommendation effect is better, and the activity types preferred by the user are counted by the application program in the mobile terminal used by the user daily, so that the daily needs of the user for various types of activities can be truly reflected, and the preference of the user is accurately positioned.
Compared with the fifth embodiment, in consideration of the fact that the user may generate preferences for a plurality of types of activities, statistics of the preference of the user for the preferred activity types are increased, when a plurality of different types of activities preferred by the user are recommended to the user, the activities preferred by the different types of users can be ranked according to the preference and then recommended to the user, and the use experience of the user is further improved.
A seventh embodiment of the present invention, a mobile terminal, can be understood as an entity device, as shown in fig. 6, including a processor 10 and a memory 20 storing instructions executable by the processor 10, and when the instructions are executed by the processor 10, the following operations are performed:
determining the activity type preferred by the user according to the use condition of each application program on the mobile terminal;
acquiring activity information which is the same as the activity type preferred by the user from the Internet;
screening out activity information matched with the daily life state of the user according to the acquired activity information and recommending the activity information; the daily living states of the user include: the user's leisure time.
Optionally, the user's leisure time includes: the user's own scheduled vacation time, and/or the national legal vacation.
Optionally, the daily life state of the user further includes at least one of: the method comprises the following steps of (1) obtaining the current position of a user, the common trip route of the user, the preset trip route of the user and the number of family members of the user;
the processor 10 performs operations further comprising: acquiring a common travel route of the user or a preset travel route of the user in the following way:
obtaining route input information according to an application program related to traffic travel in the using process; alternatively, input information at a set frequent occurrence route information entry or a scheduled travel route entry is received.
An eighth embodiment of the present invention is an application example of the present invention, which is described with reference to fig. 7 by taking a mobile phone as an example on the basis of the above embodiments.
The information recommendation method of the embodiment of the invention comprises the following two stages:
the first stage is as follows: the user is accustomed to learning.
And collecting and mining big data according to the type of the application program App used by the user in the mobile phone every day and the information of using the App, and collecting and analyzing the big data for a long time to form a set of life habit information of the user.
Through the analysis of the big data, the preference of the user can be obtained; the route of the user for frequent trip can be obtained through the trip route of the user; the number of family members of the user can be analyzed according to the daily life habits of the user.
And a second stage: and (6) activity recommendation.
The statistical classification is carried out according to the times of opening App of a specific activity or viewing information of the specific activity by a user, and the statistical classification is divided into a plurality of grades according to the times, for example: the 100 times, 50 times and 10 times correspond to the likes of great interest, likes of great interest and likes of tendency, respectively. The system can focus on the preference with high level of attention according to the level liked by the user, and provides more accurate and interested activity recommendation for the user. Such as:
A. if the user likes to visit a shopping mall, the activity information can be pushed to the user when the user has related activities in a surrounding shopping mall or a shopping mall where the user often approaches a route.
B. When the user likes ball operation, if the user lives with ball activity around, the user can be forecasted and pushed for the first time.
C. When a weekend or a legal vacation comes, different travel packages can be recommended according to the number of the family members of the user, and the problem that the user does not know to arrange activities once the user goes to the vacation is solved.
As shown in fig. 7, the information recommendation method according to the embodiment of the present invention includes the following steps:
step 1, learning user habit information through big data collection and statistics and obtaining the activity type and the preference degree preferred by the user. The user habit information includes: leisure time of the user, the current position of the user, a common travel route of the user, a preset travel route of the user, the number of family members of the user and the like;
and 2, collecting activities preferred by the user and matched with the user habit information on the Internet.
And 3, recommending activities to the user according to the user habit information and the temporary travel plan of the user, and sorting according to the preference degree when more than one activity type exists.
Through the scheme, a large amount of favorite activity recommendation information can be provided for the user, the daily life of the user is enriched, the user experience is improved, and the product market competitiveness is invisibly enhanced.
In a ninth embodiment of the present invention, a flow of a method for recommending information to a user by a mobile terminal of this embodiment is the same as that in the first, second, or third embodiments, but the difference is that in terms of engineering implementation, this embodiment can be implemented by software plus a necessary general hardware platform, and certainly, the present embodiment can also be implemented by hardware, but the former is a better implementation manner in many cases. With this understanding in mind, the method of the present invention may be embodied in the form of a computer software product stored on a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and including instructions for causing a device (e.g., mobile terminal such as a mobile phone) to perform the method of the present invention.
While the invention has been described in connection with specific embodiments thereof, it is to be understood that it is intended by the appended drawings and description that the invention may be embodied in other specific forms without departing from the spirit or scope of the invention.
Claims (10)
1. A method for information recommendation, comprising:
determining the activity type preferred by the user according to the use condition of each application program on the mobile terminal;
acquiring activity information which is the same as the activity type preferred by the user from the Internet;
screening out activity information matched with the daily life state of the user according to the acquired activity information and recommending the activity information; the daily living states of the user include: the method comprises the following steps of (1) obtaining a common travel route of a user, a preset travel route of the user and the number of family members of the user;
the obtaining mode of the common travel route of the user or the preset travel route of the user comprises the following steps:
obtaining route input information according to an application program related to traffic travel in the using process; or receiving input information at a set common travel route information entry place or a preset travel route entry place;
the determining the activity type preferred by the user according to the use condition of each application program on the mobile terminal comprises the following steps:
presetting a first corresponding relation between an application program and an activity type; determining the activity type preferred by the user according to the collected use frequency of each application program on the mobile terminal on the basis of the first corresponding relation; or determining the activity type preferred by the user according to the collected checking frequency of the activity information of the set activity type in each application program;
obtaining activity information from the internet that is the same as the user's preferred activity type, further comprising: filtering the acquired activity information.
2. The method of information recommendation according to claim 1, wherein said activity type comprises at least one of: shopping activities, sports activities, entertainment activities, tourism activities.
3. The method of information recommendation according to claim 2, further comprising:
presetting a second corresponding relation between the use frequency and the preference degree or checking the second corresponding relation between the use frequency and the preference degree;
and determining the preference degree of the user for the preferred activity type according to the second corresponding relation.
4. The method of claim 1, wherein the obtaining activity information from the internet that is the same as the user's preferred activity type comprises:
and acquiring activity information which is the same as the activity type preferred by the user from the Internet through a web crawler tool.
5. The information recommendation method according to claim 3, wherein the screening out and recommending activity information matching with the daily life state of the user according to the acquired activity information comprises:
and when the types of the screened activity information matched with the daily life state of the user are more than two, sorting and recommending the screened activity information according to the preference degree of the user to each activity type preferred.
6. An apparatus for information recommendation, comprising:
the first determining module is used for determining the activity type preferred by the user according to the use condition of each application program on the mobile terminal;
the acquisition module is used for acquiring activity information which is the same as the activity type favored by the user from the Internet;
the recommendation module is used for screening out activity information matched with the daily life state of the user according to the acquired activity information and recommending the activity information; the daily living states of the user include: the method comprises the following steps of (1) obtaining a common travel route of a user, a preset travel route of the user and the number of family members of the user;
the obtaining module is further configured to obtain a common travel route of the user or a predetermined travel route of the user in the following manner:
obtaining route input information according to an application program related to traffic travel in the using process; or receiving input information at a set common travel route information entry place or a preset travel route entry place;
the first determining module is configured to:
presetting a first corresponding relation between an application program and an activity type; determining the activity type preferred by the user according to the collected use frequency of each application program on the mobile terminal on the basis of the first corresponding relation; or determining the activity type preferred by the user according to the collected checking frequency of the activity information of the set activity type in each application program;
and the acquisition module is also used for filtering the acquired activity information.
7. The information recommendation device of claim 6,
the activity type includes at least one of: shopping activities, sports activities, entertainment activities, tourism activities.
8. The apparatus for information recommendation according to claim 7, further comprising:
the second determining module is used for presetting a second corresponding relation between the use frequency and the preference degree or checking the second corresponding relation between the use frequency and the preference degree; and determining the preference degree of the user for the preferred activity type according to the second corresponding relation.
9. The apparatus for information recommendation according to claim 6, wherein said obtaining module is configured to obtain the activity information with the same activity type as the user's preference from the internet through a web crawler tool.
10. The apparatus of claim 8, wherein the recommendation module is configured to:
and when the types of the screened activity information matched with the daily life state of the user are more than two, sorting and recommending the screened activity information according to the preference degree of the user to each activity type preferred.
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| CN107943884A (en) * | 2017-11-15 | 2018-04-20 | 河南工学院 | The processing method and processing unit of travel information |
| CN108347704A (en) * | 2018-01-24 | 2018-07-31 | 维沃移动通信有限公司 | Information recommendation method and mobile terminal |
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| CN110457607A (en) * | 2019-08-05 | 2019-11-15 | 北京字节跳动网络技术有限公司 | A kind of partial journey information recommendation method, device, medium and electronic equipment |
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