CN102385636A - Intelligent searching method and device - Google Patents
Intelligent searching method and device Download PDFInfo
- Publication number
- CN102385636A CN102385636A CN2011104350015A CN201110435001A CN102385636A CN 102385636 A CN102385636 A CN 102385636A CN 2011104350015 A CN2011104350015 A CN 2011104350015A CN 201110435001 A CN201110435001 A CN 201110435001A CN 102385636 A CN102385636 A CN 102385636A
- Authority
- CN
- China
- Prior art keywords
- user
- interest
- information
- point
- demand
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
Abstract
The invention discloses an intelligent searching method and device. The method comprises the following steps of: step 1, acquiring the current position information of a user; step 2, searching for interesting point information and/or event information directed at the user through a customized searching model corresponding to the user according to the current position information and the current time, wherein the customized searching model is obtained by executing demand analysis of each period of time on the base population of the user; and step 3, transferring the interesting point information and/or the event information to the user. Through the method and device disclosed by the invention, the user can get the interesting point information and the event information based on user characteristics without executing input operations, so that the life information demand of the user can be satisfied conveniently and accurately.
Description
Technical field
The present invention relates to intelligent search technique, particularly relate to a kind of intelligent search method and apparatus.
Background technology
Current society, network is popularized, and this has brought huge quantity of information, and in the information ocean of vastness, the only reliable search engine of people (search engine) just can be unlikely to get lost, and could find required information rapidly.So-called search engine is meant according to certain strategy, the specific computer program of utilization to gather information from the internet that after information being organized and handled, for the user provides retrieval service, user's system is given in the information exhibition that user search is relevant.
Intelligent searching engine is the search engine of new generation that has combined artificial intelligence technology.He be except providing functions such as traditional quick retrieval, relevancy ranking, can also provide that user role registration, user interest are discerned automatically, the functions such as semantic understanding, intelligent information filtration and propelling movement of content.
Existing intelligent searching engine technology mainly comprises:
(1) keyword search and the semantic search of deriving thereof are the technological means that existing user obtains information.This technology relies on user's input, carries out relevant search in the system database the inside then, provides the result to the user then.
The major defect of the keyword search and the semantic search of deriving thereof has:
1, user's craft of this Technology Need or phonetic entry key word, word have input slow on mobile device, occur mistake or the like easily.
2, this Technology Need key word, word, but the user's request that has can't be explained out with limited key word.
(2) based on the data acquisition technology in user geographic position.This technology through obtaining user's geographical location information, is retrieved in database then, then presents to the user to the result with consumption classification or the far and near isotactic of distance then.
Shortcoming based on the data acquisition technology in user geographic position is:
1, just Search Results is simply enumerated, can not be shown according to the true intention of factor judges such as time, incident, user characteristics.
2, the user need take time and browse the information that obtains, and oneself screens, and efficient is not high.
Summary of the invention
The purpose of the embodiment of the invention provides a kind of intelligent search method and apparatus, need not user's input operation and just can obtain interest point information, event information based on user's unique characteristics, can make things convenient for the life information demand that satisfies the user accurately.
To achieve these goals, the invention provides a kind of intelligent search method, comprising:
Step 1 is obtained user's current location information;
Preferably, in the above-mentioned method, said customized searches model comprises:
Attention rate according to the basic crowd's computation requirement under the said user; Be transverse axis Time Created; Attention rate is that the demand of the longitudinal axis is paid close attention to curve, and pays close attention to the demand order of just arranging according to attention rate numerical value that curve obtains current point in time according to the demand of different demands;
Various demands are carried out class definition, and set up corresponding relation with point of interest.
Preferably, in the above-mentioned method,
Confirm the basic crowd under the said user according to said user's user characteristics;
Said user characteristics comprises:, initiatively mode such as the interpolations age parameter, sex parameter, the professional parameter that obtain and/or like parameter interactive through user's registration, operational analysis, question and answer.
Preferably; In the above-mentioned method; Also comprise; Through point of interest regional influence model said customized searches model is revised, said point of interest regional influence model comprises: decay radius and the die-away curve of confirming influence power according to the rank and the type of point of interest, and according to the attention rate between point of interest and said user's the current location apart from correction demand and point of interest.
Preferably, in the above-mentioned method, comprise also that through the disturbance factor model said customized searches model is revised, said disturbance factor model comprises: according to the attention rate of objective event correction demand and point of interest.
Preferably, in the above-mentioned method, said objective event comprises known event that presets and the accident of obtaining;
The said known event that presets is: season, season, solar term, red-letter day and/or local custom;
Said accident of obtaining is: weather, traffic, social news incident and/or trend focus.
Preferably, in the above-mentioned method, comprise also that the said user through daily accumulative total revises said customized searches model in the frequency of occurrences and the time of occurrence section of ad-hoc location or point of interest position.
Preferably, in the above-mentioned method, also comprise in the said step 3,, confirm display category, the show bar number of said interest point information and/or event information and/or put in order according to said user's user characteristics;
Said interest point information comprises: title, classification, longitude, latitude and phone;
Said interest point information also comprises: experience comment, dynamically preferential, encyclopaedic knowledge and/or special topic;
Said event information is: traffic, social news incident and/or trend focus.
The present invention also provides a kind of intelligent search device, comprising:
The information acquisition module is used for: the current location information that obtains the user;
Search module is used for: according to said current location information and current time, search for through the said user's of correspondence customized searches model, obtain interest point information and/or event information to said user; Wherein, said customized searches model is to obtain through the basic crowd under the said user is carried out the demand analysis of each time period;
Push module, be used for: said interest point information and/or event information are pushed to said user.
Preferably; In the above-mentioned device; Said information acquisition module also is used for: under the prerequisite that the user knows the inside story, obtain user's age parameter, sex parameter, professional parameter and/or hobby parameter through modes such as user's registration, operational analysis, question and answer interaction, active interpolations; Under the prerequisite that the user knows the inside story, when user's login or updating software, obtain user's time and User Identity number;
Said search module comprises: MBM; Be used for: according to the attention rate of the basic crowd's computation requirement under the said user; Be transverse axis Time Created; Attention rate is that the demand of the longitudinal axis is paid close attention to curve, and pays close attention to the demand order of just arranging according to attention rate numerical value that curve obtains current point in time according to the demand of different demands; Demand coding knock-down module is used for: various demands are carried out class definition, and set up corresponding relation with point of interest;
Said MBM also is used for: through point of interest regional influence model said customized searches model is revised; Through the disturbance factor model said customized searches model is revised; Said user through daily accumulative total revises said customized searches model in the frequency of occurrences and the time of occurrence section of ad-hoc location, point of interest position;
Said propelling movement module also is used for: according to said user's user characteristics, confirm display category, the show bar number of said interest point information and/or event information and/or put in order; Said interest point information comprises: title, classification, longitude, latitude and phone; Said interest point information also comprises: experience comment, dynamically preferential, encyclopaedic knowledge and/or special topic.
There is following technique effect at least in the embodiment of the invention:
1) user need not to import interest point information, the event information that keyword just can obtain position-based, time, unique characteristics in the embodiment of the invention; Thereby input trouble, the keyword that can solve prior art are inaccurate, user profile is obtained defectives such as inaccurate, and then can help the acquisition life information and the service of user's convenient and efficient.
2) embodiment of the invention is that behavioural characteristic to each user constantly accumulates; Set up personalized demand model for it; And the technology of the service for life information that meets its demand is provided; It is not the searching request that passive wait user proposes key word, but position-based, time, person model and characteristic are to the maximally related service for life information of the convenient propelling movement of user.
In a word, the embodiment of the invention through user modeling and demand analysis, can be excavated user's real demand to greatest extent, to the user him is provided information of interest, has greatly improved the efficient that user profile is obtained.
Description of drawings
Fig. 1 is the flow chart of steps of the inventive method embodiment;
Fig. 2 is an intelligent search structure drawing of device provided by the invention;
Fig. 3 is that demand provided by the invention is paid close attention to curve;
Fig. 4 is a demand sequential schematic of just arranging according to attention rate provided by the invention.
Embodiment
For the purpose, technical scheme and the advantage that make the embodiment of the invention is clearer, will combine accompanying drawing that specific embodiment is described in detail below.
Fig. 1 is the flow chart of steps of the inventive method embodiment, and is as shown in Figure 1, and the embodiment of the invention provides a kind of intelligent search method, and it comprises:
It is thus clear that; The embodiment of the invention is searched for through current location and customized searches model; The user need not to import keyword just can obtain interest point information or event information based on unique characteristics; Thereby input trouble, the keyword that can solve prior art are inaccurate, user profile is obtained defectives such as inaccurate, and then can help the acquisition life information and the service of user's convenient and efficient.
Wherein, Said customized searches model comprises: according to the attention rate of the basic crowd's computation requirement under the said user; Be transverse axis Time Created, and attention rate is that the demand of the longitudinal axis is paid close attention to curve, and form the putting in order of attention rate numerical value height of various demands based on this; Various demands are carried out class definition, and set up corresponding relation with point of interest.
Fig. 3 is that demand provided by the invention is paid close attention to curve, and is as shown in Figure 3.Its demonstration be the see a film changes in demand of a certain user (the for example women of profession) in some weekends (for example on Dec 16th, 2011).Wherein, Time is transverse axis, and the attention rate of the demand of seeing a film is the longitudinal axis, can find out; The attention rate of seeing a film in 16 o'clock to 18 o'clock is bigger; This period is paid close attention to movie news most and makes the decision of going to the cinema more easily, and the attention rate that the period in morning sees a film is just very little, because this period common people are in sleep.
Fig. 4 is a demand sequential schematic of just arranging according to attention rate provided by the invention.As shown in the figure, the demand of a certain user's (the for example women of profession) various demands is paid close attention to curve cut into slices, can obtain attention rate in sometime various demands; After just arranging according to attention rate; Just knowing that in the maximum demand of this time point user be that those are several, for example, is the demand order of 6 pm clock among Fig. 4; This time point, the maximum demand of user is to have dinner, see a film and go window-shopping.
Wherein, confirm the basic crowd under the said user according to said user's user characteristics; Said user characteristics comprises:, initiatively mode such as the interpolations age parameter, sex parameter, the professional parameter that obtain and/or like parameter interactive through user's registration, operational analysis, question and answer.
Comprise that also the said user through daily accumulative total revises said customized searches model in the frequency of occurrences and the time of occurrence section of ad-hoc location or point of interest position.
Therefore; The embodiment of the invention is that the behavioural characteristic to each user constantly accumulates; Set up personalized demand model for it; And the technology of the service for life information that meets its demand is provided, it is not the searching request that passive wait user proposes key word, but position-based, time, person model and characteristic are to the maximally related service for life information of the convenient propelling movement of user.
Among the present invention; Not only obtain customized searches model to the user through user's demand being carried out analysis modeling; Also modeling has been carried out in the influence of demand to point of interest itself and external condition; Obtain point of interest regional influence model and disturbance factor model, thereby can hold user's request more accurately.
Therefore; In the embodiment of the invention; Also comprise; Through point of interest regional influence model said customized searches model is revised, said point of interest regional influence model comprises: according to decay radius and the die-away curve that the rank and the type of point of interest are confirmed influence power, revise the attention rate of point of interest according to the distance between point of interest and said user's the current location.
For example, the user generally refuels nearby, and the distance of distance is very big to customer impact, so the desirability of refuelling station decay with the prolongation meeting of distance very soon, and its die-away curve is just very steep, and the radius of decaying is very little.
Again for example, for a first visitor who comes to Beijing, though far apart from some sight spots, even Tian An-men, the Summer Palace, these well-known sight spots, Great Wall still do not have very big attention rate nearby yet, therefore well-known tourist attractions decay radius is very big.
In the embodiment of the invention, comprise also that through the disturbance factor model said customized searches model is revised, said disturbance factor model comprises: according to the attention rate of objective event correction point of interest.
Wherein, said objective event comprises known event that presets and the accident of obtaining;
The said known event that presets is: season, season, solar term, red-letter day and/or local custom;
Said accident of obtaining is: weather, traffic, social news incident and/or trend focus.
For example, in the Dragon Boat Festival, the attention rate that can eat the restaurant of pyramid-shaped dumpling can rise, and in the winter time, the attention rate of cold drink shop can descend.During the SARS epidemic situation, the attention rate of pharmacy and hospital can rise.
In addition, the present invention gives the user stiff interest point information simple push, also comprises in the said step 103, according to said user's user characteristics, confirms display category, the show bar number of said interest point information and/or puts in order; Said interest point information not only comprises: title, classification, longitude and latitude, phone, and can also extra comprising: experience comment, dynamically preferential, encyclopaedic knowledge and/or special topic.Said event information is: traffic, social news incident and/or trend focus
Fig. 2 is intelligent search structure drawing of device provided by the invention, and is as shown in Figure 2, and the intelligent search device comprises:
Wherein, Said search module also is used for: through point of interest regional influence model said customized searches model is revised; Through the disturbance factor model said customized searches model is revised; Said user through daily accumulative total revises said customized searches model in the frequency of occurrences and the time of occurrence section of ad-hoc location, point of interest position.
It is thus clear that the modeler model of using in the intelligent search device mainly contains following several kinds:
1) the customized searches model of respective user comprises character features modeling and the modeling of personage's primary demand.
Character features modeling: its foundation and user's interaction, use preference and means such as data analysis, key word active maintenance progressively to accumulate user characteristics, and confirm influence value for various demands concern curves.
Personage's primary demand modeling: carry out sorting code number, formation tens, hundreds of or thousands of demand coding schedules with the relevant primary demand of consumption to human.Compile the different crowd demand period of right time according to sex, residence, time degree of freedom equal angles, and to formulate with time with this be transverse axis, attention rate is that the demand of the longitudinal axis is paid close attention to curve.
2) point of interest regional influence model, just POI (Point of Interest point of interest) and regional effect force modeling
It is implemented the link code operation to concrete POI and zone, and confirms its influence value for demand according to demand coding and POI characteristics; Confirm its influence power decay radius according to the POI rank; Calculate the field of force that influences of the interior POI in each zone, city with this.
3) disturbance factor modeling
Set the curve of influence value pay close attention to to(for) various demands according to predictable objective fact (like season, season, solar term, red-letter day, local custom etc.) and uncertain objective fact (like weather, traffic, social event, trend focus etc.).
Above model constitutes the core engine of intelligent search, with above demand concern value and influence factor stack thereof, draws the user and pays close attention to sequence in the demand of special period locality.
In addition, push module 203 and have following information demonstration rule: the user can send geographical location information, and time point information is pushed to server (being intelligent search device of the present invention) automatically and handles; Server is paid close attention to sequence according to the demand that core engine generates the special period locality; Show that according to information rule accesses customizing messages from content data base then.Information shows rule because of personage's type and whether permanent residence has a great difference, the main display category of regulation demand, show bar number, puts in order etc.Content with experience comment, dynamically presented such as preferential, thematic encyclopaedia is main, is not stiff POI brief introduction.
By on can know that the embodiment of the invention has following advantage:
1) user need not to import keyword and just can obtain interest point information and event information based on unique characteristics in the embodiment of the invention; Thereby input trouble, the keyword that can solve prior art are inaccurate, user profile is obtained defectives such as inaccurate, and then can help the acquisition life information and the service of user's convenient and efficient.
2) embodiment of the invention is that behavioural characteristic to each user constantly accumulates; Set up personalized demand model for it; And the technology of the service for life information that meets its demand is provided; It is not the searching request that passive wait user proposes key word, but position-based, time, person model and characteristic are to the maximally related service for life information of the convenient propelling movement of user.
In a word, the embodiment of the invention through user modeling and demand analysis, can be excavated user's real demand to greatest extent, to the user him is provided information of interest, has greatly improved the efficient that user profile is obtained.
The above only is a preferred implementation of the present invention; Should be pointed out that for those skilled in the art, under the prerequisite that does not break away from the principle of the invention; Can also make some improvement and retouching, these improvement and retouching also should be regarded as protection scope of the present invention.
Claims (10)
1. an intelligent search method is characterized in that, comprising:
Step 1 is obtained user's current location information;
Step 2 according to said current location information and current time, is searched for through the said user's of correspondence customized searches model, obtains interest point information and/or event information to said user; Wherein, said customized searches model is to obtain through the basic crowd under the said user is carried out the demand analysis of each time period;
Step 3 is pushed to said user with said interest point information and/or event information.
2. intelligent search method according to claim 1 is characterized in that, said customized searches model comprises:
Attention rate according to the basic crowd's computation requirement under the said user; Be transverse axis Time Created; Attention rate is that the demand of the longitudinal axis is paid close attention to curve, and pays close attention to the demand order of just arranging according to attention rate numerical value that curve obtains current point in time according to the demand of different demands;
Various demands are carried out class definition, and set up corresponding relation with point of interest.
3. intelligent search method according to claim 2 is characterized in that,
Confirm the basic crowd under the said user according to said user's user characteristics;
Said user characteristics comprises:, initiatively mode such as the interpolations age parameter, sex parameter, the professional parameter that obtain and/or like parameter interactive through user's registration, operational analysis, question and answer.
4. intelligent search method according to claim 2; It is characterized in that; Also comprise; Through point of interest regional influence model said customized searches model is revised, said point of interest regional influence model comprises: decay radius and the die-away curve of confirming influence power according to the rank and the type of point of interest, and according to the attention rate between point of interest and said user's the current location apart from correction demand and point of interest.
5. intelligent search method according to claim 2 is characterized in that, also comprises, through the disturbance factor model said customized searches model is revised, and said disturbance factor model comprises: according to the attention rate of objective event correction demand and point of interest.
6. intelligent search method according to claim 5 is characterized in that, said objective event comprises known event that presets and the accident of obtaining;
The said known event that presets is: season, season, solar term, red-letter day and/or local custom;
Said accident of obtaining is: weather, traffic, social news incident and/or trend focus.
7. intelligent search method according to claim 2 is characterized in that, also comprises, the said user through daily accumulative total revises said customized searches model in the frequency of occurrences and the time of occurrence section of ad-hoc location or point of interest position.
8. intelligent search method according to claim 3 is characterized in that,
Also comprise in the said step 3,, confirm display category, the show bar number of said interest point information and/or event information and/or put in order according to said user's user characteristics;
Said interest point information comprises: title, classification, longitude, latitude and phone;
Said interest point information also comprises: experience comment, dynamically preferential, encyclopaedic knowledge and/or special topic;
Said event information is: traffic, with relevant social news incident and/or the trend focus of consumption.
9. an intelligent search device is characterized in that, comprising:
The information acquisition module is used for: the current location information that obtains the user;
Search module is used for: according to said current location information and current time, search for through the said user's of correspondence customized searches model, obtain interest point information and/or event information to said user; Wherein, said customized searches model is to obtain through the basic crowd under the said user is carried out the demand analysis of each time period;
Push module, be used for: said interest point information and/or event information are pushed to said user.
10. intelligent search device according to claim 9 is characterized in that,
Said information acquisition module also is used for: under the prerequisite that the user knows the inside story, obtain user's age parameter, sex parameter, professional parameter and/or hobby parameter through modes such as user's registration, operational analysis, question and answer interaction, active interpolations; Under the prerequisite that the user knows the inside story, when user's login or updating software, obtain user's time and User Identity number;
Said search module comprises: MBM; Be used for: according to the attention rate of the basic crowd's computation requirement under the said user; Be transverse axis Time Created; Attention rate is that the demand of the longitudinal axis is paid close attention to curve, and pays close attention to the demand order of just arranging according to attention rate numerical value that curve obtains current point in time according to the demand of different demands; Demand coding knock-down module is used for: various demands are carried out class definition, and set up corresponding relation with point of interest;
Said MBM also is used for: through point of interest regional influence model said customized searches model is revised; Through the disturbance factor model said customized searches model is revised; Said user through daily accumulative total revises said customized searches model in the frequency of occurrences and the time of occurrence section of ad-hoc location, point of interest position;
Said propelling movement module also is used for: according to said user's user characteristics, confirm display category, the show bar number of said interest point information and/or event information and/or put in order; Said interest point information comprises: title, classification, longitude, latitude and phone; Said interest point information also comprises: experience comment, dynamically preferential, encyclopaedic knowledge and/or special topic.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2011104350015A CN102385636A (en) | 2011-12-22 | 2011-12-22 | Intelligent searching method and device |
| PCT/CN2012/071663 WO2013091302A1 (en) | 2011-12-22 | 2012-02-27 | Intelligent search method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2011104350015A CN102385636A (en) | 2011-12-22 | 2011-12-22 | Intelligent searching method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN102385636A true CN102385636A (en) | 2012-03-21 |
Family
ID=45825052
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2011104350015A Pending CN102385636A (en) | 2011-12-22 | 2011-12-22 | Intelligent searching method and device |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN102385636A (en) |
| WO (1) | WO2013091302A1 (en) |
Cited By (34)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102984219A (en) * | 2012-11-13 | 2013-03-20 | 浙江大学 | Tourism mobile terminal information pushing method based on medial multi-dimensional content expression |
| CN103077489A (en) * | 2013-01-22 | 2013-05-01 | 苏州海客科技有限公司 | Prediction method of random demands of tourist user |
| CN103236163A (en) * | 2013-04-28 | 2013-08-07 | 北京航空航天大学 | Traffic jam avoiding prompting system based on collective intelligence network |
| CN103729387A (en) * | 2012-10-16 | 2014-04-16 | 北京糯米网科技发展有限公司 | Data push method and device |
| CN103793521A (en) * | 2014-02-18 | 2014-05-14 | 腾讯科技（深圳）有限公司 | Method and device for processing picture |
| CN103886105A (en) * | 2014-04-11 | 2014-06-25 | 北京工业大学 | User influence analysis method based on social network user behaviors |
| CN103955534A (en) * | 2014-05-13 | 2014-07-30 | 百度在线网络技术（北京）有限公司 | Map query method and device thereof |
| CN104008184A (en) * | 2014-06-10 | 2014-08-27 | 百度在线网络技术（北京）有限公司 | Method and device for pushing information |
| CN104105061A (en) * | 2014-07-21 | 2014-10-15 | 广州唯品会网络技术有限公司 | Information pushing method and system |
| CN104102433A (en) * | 2013-04-12 | 2014-10-15 | 杭州脸脸会网络技术有限公司 | Roller interaction based point-of-interest positioning method |
| CN104541527A (en) * | 2012-06-22 | 2015-04-22 | 谷歌公司 | Inferring user interests |
| CN104574146A (en) * | 2014-12-31 | 2015-04-29 | 浙江大学 | Service recommending method and system |
| CN104978700A (en) * | 2015-06-29 | 2015-10-14 | 昆明理工大学 | Real-time recommendation method for self-help travel of old people in tourism website |
| CN105045883A (en) * | 2015-07-21 | 2015-11-11 | 惠州Tcl移动通信有限公司 | Mobile terminal and search method thereof |
| CN105119743A (en) * | 2015-08-07 | 2015-12-02 | 百度在线网络技术（北京）有限公司 | Acquisition method of user behavior intention and apparatus |
| CN105359137A (en) * | 2013-06-13 | 2016-02-24 | 微软技术许可有限责任公司 | Anticipatory delivery of search results via notifications |
| CN105528353A (en) * | 2014-09-29 | 2016-04-27 | 贝壳网际（北京）安全技术有限公司 | News searching method and apparatus |
| CN105912669A (en) * | 2012-09-20 | 2016-08-31 | 北京奇虎科技有限公司 | Method and device for complementing search terms and establishing individual interest model |
| CN106331040A (en) * | 2015-07-01 | 2017-01-11 | 北汽福田汽车股份有限公司 | Method and system for making recommendation to user |
| WO2017049760A1 (en) * | 2015-09-25 | 2017-03-30 | 百度在线网络技术（北京）有限公司 | Search result processing method, apparatus and device, and computer storage medium |
| CN106777169A (en) * | 2016-12-21 | 2017-05-31 | 北京车网互联科技有限公司 | A kind of user's trip hobby analysis method based on car networking data |
| CN106909560A (en) * | 2015-12-23 | 2017-06-30 | 香港中文大学 | Point of interest sort method |
| CN106936864A (en) * | 2015-12-29 | 2017-07-07 | 国网智能电网研究院 | A kind of privacy of user guard method and system |
| CN107045500A (en) * | 2016-02-05 | 2017-08-15 | 上海行邑信息科技有限公司 | The program installation control method and device of a kind of context relation |
| CN107480162A (en) * | 2017-06-15 | 2017-12-15 | 北京百度网讯科技有限公司 | Searching method, device, equipment and computer-readable recording medium based on artificial intelligence |
| CN107562748A (en) * | 2016-06-30 | 2018-01-09 | 上海博泰悦臻网络技术服务有限公司 | Electronic equipment and its information-pushing method and system of application |
| CN107679934A (en) * | 2017-08-31 | 2018-02-09 | 北京锋景卓越科技有限公司 | A kind of travel information method for pushing and server |
| WO2018076695A1 (en) * | 2016-10-31 | 2018-05-03 | 上海斐讯数据通信技术有限公司 | Smart recommendation system and smart recommendation method |
| CN108519997A (en) * | 2018-03-07 | 2018-09-11 | 阿里巴巴集团控股有限公司 | The recommendation method and device of related content |
| CN109688545A (en) * | 2018-11-12 | 2019-04-26 | 中国人民大学 | Group's K-NN search method, first terminal, second terminal and server |
| US10332019B2 (en) | 2012-06-22 | 2019-06-25 | Google Llc | Ranking nearby destinations based on visit likelihoods and predicting future visits to places from location history |
| CN110399568A (en) * | 2019-07-04 | 2019-11-01 | Oppo广东移动通信有限公司 | Information search method, device, terminal and storage medium |
| CN111191151A (en) * | 2019-12-20 | 2020-05-22 | 上海淇玥信息技术有限公司 | Method and device for pushing information based on POI (Point of interest) tag and electronic equipment |
| WO2021092922A1 (en) * | 2019-11-15 | 2021-05-20 | 深圳市欢太科技有限公司 | Information pushing method and apparatus, server and computer-readable medium |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103916476A (en) * | 2014-04-08 | 2014-07-09 | 百度在线网络技术（北京）有限公司 | Information pushing method and device based on position |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1858733A (en) * | 2005-11-01 | 2006-11-08 | 华为技术有限公司 | Information searching system and searching method |
| CN101114294A (en) * | 2007-08-22 | 2008-01-30 | 杭州经合易智控股有限公司 | Self-help intelligent uprightness searching method |
| CN101627384A (en) * | 2007-03-08 | 2010-01-13 | 微软公司 | From search inquiry, detect user's position, local intention and travel intent |
| CN101937437A (en) * | 2009-06-30 | 2011-01-05 | 华为技术有限公司 | Search method, device and system |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101896902A (en) * | 2007-12-13 | 2010-11-24 | 大日本印刷株式会社 | Information providing system |
| CN101866341A (en) * | 2009-04-17 | 2010-10-20 | 华为技术有限公司 | Information push method, device and system |
| WO2010138775A1 (en) * | 2009-05-27 | 2010-12-02 | Geodelic, Inc. | Location discovery system and method |
-
2011
- 2011-12-22 CN CN2011104350015A patent/CN102385636A/en active Pending
-
2012
- 2012-02-27 WO PCT/CN2012/071663 patent/WO2013091302A1/en active Application Filing
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1858733A (en) * | 2005-11-01 | 2006-11-08 | 华为技术有限公司 | Information searching system and searching method |
| CN101627384A (en) * | 2007-03-08 | 2010-01-13 | 微软公司 | From search inquiry, detect user's position, local intention and travel intent |
| CN101114294A (en) * | 2007-08-22 | 2008-01-30 | 杭州经合易智控股有限公司 | Self-help intelligent uprightness searching method |
| CN101937437A (en) * | 2009-06-30 | 2011-01-05 | 华为技术有限公司 | Search method, device and system |
Cited By (46)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10332019B2 (en) | 2012-06-22 | 2019-06-25 | Google Llc | Ranking nearby destinations based on visit likelihoods and predicting future visits to places from location history |
| CN104541527A (en) * | 2012-06-22 | 2015-04-22 | 谷歌公司 | Inferring user interests |
| CN104541527B (en) * | 2012-06-22 | 2019-01-29 | 谷歌有限责任公司 | For inferring the method for the interest of user and calculating equipment |
| CN105912669A (en) * | 2012-09-20 | 2016-08-31 | 北京奇虎科技有限公司 | Method and device for complementing search terms and establishing individual interest model |
| CN103729387A (en) * | 2012-10-16 | 2014-04-16 | 北京糯米网科技发展有限公司 | Data push method and device |
| CN102984219A (en) * | 2012-11-13 | 2013-03-20 | 浙江大学 | Tourism mobile terminal information pushing method based on medial multi-dimensional content expression |
| CN102984219B (en) * | 2012-11-13 | 2015-09-09 | 浙江大学 | A kind of travel mobile terminal information-pushing method of expressing based on media multi-dimensional content |
| CN103077489A (en) * | 2013-01-22 | 2013-05-01 | 苏州海客科技有限公司 | Prediction method of random demands of tourist user |
| CN104102433A (en) * | 2013-04-12 | 2014-10-15 | 杭州脸脸会网络技术有限公司 | Roller interaction based point-of-interest positioning method |
| CN103236163A (en) * | 2013-04-28 | 2013-08-07 | 北京航空航天大学 | Traffic jam avoiding prompting system based on collective intelligence network |
| CN105359137A (en) * | 2013-06-13 | 2016-02-24 | 微软技术许可有限责任公司 | Anticipatory delivery of search results via notifications |
| CN103793521A (en) * | 2014-02-18 | 2014-05-14 | 腾讯科技（深圳）有限公司 | Method and device for processing picture |
| CN103793521B (en) * | 2014-02-18 | 2018-04-27 | 腾讯科技（深圳）有限公司 | Image processing method and device |
| CN103886105A (en) * | 2014-04-11 | 2014-06-25 | 北京工业大学 | User influence analysis method based on social network user behaviors |
| CN103886105B (en) * | 2014-04-11 | 2017-05-17 | 北京工业大学 | User influence analysis method based on social network user behaviors |
| CN103955534A (en) * | 2014-05-13 | 2014-07-30 | 百度在线网络技术（北京）有限公司 | Map query method and device thereof |
| WO2015172578A1 (en) * | 2014-05-13 | 2015-11-19 | 百度在线网络技术（北京）有限公司 | Map query method, device, equipment and computer storage medium |
| US10210161B2 (en) | 2014-05-13 | 2019-02-19 | Baidu Online Network Technology (Beijing) Co., Ltd. | Method and device for inquiring map |
| CN103955534B (en) * | 2014-05-13 | 2017-08-04 | 百度在线网络技术（北京）有限公司 | Map inquiry method and device |
| CN104008184A (en) * | 2014-06-10 | 2014-08-27 | 百度在线网络技术（北京）有限公司 | Method and device for pushing information |
| CN104105061A (en) * | 2014-07-21 | 2014-10-15 | 广州唯品会网络技术有限公司 | Information pushing method and system |
| CN105528353A (en) * | 2014-09-29 | 2016-04-27 | 贝壳网际（北京）安全技术有限公司 | News searching method and apparatus |
| CN104574146A (en) * | 2014-12-31 | 2015-04-29 | 浙江大学 | Service recommending method and system |
| CN104978700A (en) * | 2015-06-29 | 2015-10-14 | 昆明理工大学 | Real-time recommendation method for self-help travel of old people in tourism website |
| CN106331040A (en) * | 2015-07-01 | 2017-01-11 | 北汽福田汽车股份有限公司 | Method and system for making recommendation to user |
| CN106331040B (en) * | 2015-07-01 | 2020-01-17 | 北京宝沃汽车有限公司 | Method and system for recommending users |
| CN105045883A (en) * | 2015-07-21 | 2015-11-11 | 惠州Tcl移动通信有限公司 | Mobile terminal and search method thereof |
| CN105045883B (en) * | 2015-07-21 | 2020-12-25 | 惠州Tcl移动通信有限公司 | Mobile terminal and searching method thereof |
| WO2017024684A1 (en) * | 2015-08-07 | 2017-02-16 | 百度在线网络技术（北京）有限公司 | User behavioral intent acquisition method, device and equipment, and computer storage medium |
| CN105119743A (en) * | 2015-08-07 | 2015-12-02 | 百度在线网络技术（北京）有限公司 | Acquisition method of user behavior intention and apparatus |
| WO2017049760A1 (en) * | 2015-09-25 | 2017-03-30 | 百度在线网络技术（北京）有限公司 | Search result processing method, apparatus and device, and computer storage medium |
| CN106909560A (en) * | 2015-12-23 | 2017-06-30 | 香港中文大学 | Point of interest sort method |
| CN106936864A (en) * | 2015-12-29 | 2017-07-07 | 国网智能电网研究院 | A kind of privacy of user guard method and system |
| CN107045500A (en) * | 2016-02-05 | 2017-08-15 | 上海行邑信息科技有限公司 | The program installation control method and device of a kind of context relation |
| CN107562748A (en) * | 2016-06-30 | 2018-01-09 | 上海博泰悦臻网络技术服务有限公司 | Electronic equipment and its information-pushing method and system of application |
| WO2018076695A1 (en) * | 2016-10-31 | 2018-05-03 | 上海斐讯数据通信技术有限公司 | Smart recommendation system and smart recommendation method |
| CN106777169A (en) * | 2016-12-21 | 2017-05-31 | 北京车网互联科技有限公司 | A kind of user's trip hobby analysis method based on car networking data |
| CN107480162A (en) * | 2017-06-15 | 2017-12-15 | 北京百度网讯科技有限公司 | Searching method, device, equipment and computer-readable recording medium based on artificial intelligence |
| CN107679934A (en) * | 2017-08-31 | 2018-02-09 | 北京锋景卓越科技有限公司 | A kind of travel information method for pushing and server |
| CN108519997A (en) * | 2018-03-07 | 2018-09-11 | 阿里巴巴集团控股有限公司 | The recommendation method and device of related content |
| CN109688545B (en) * | 2018-11-12 | 2020-12-15 | 中国人民大学 | Privacy protection group nearest neighbor query method and device |
| CN109688545A (en) * | 2018-11-12 | 2019-04-26 | 中国人民大学 | Group's K-NN search method, first terminal, second terminal and server |
| CN110399568A (en) * | 2019-07-04 | 2019-11-01 | Oppo广东移动通信有限公司 | Information search method, device, terminal and storage medium |
| WO2021092922A1 (en) * | 2019-11-15 | 2021-05-20 | 深圳市欢太科技有限公司 | Information pushing method and apparatus, server and computer-readable medium |
| CN111191151A (en) * | 2019-12-20 | 2020-05-22 | 上海淇玥信息技术有限公司 | Method and device for pushing information based on POI (Point of interest) tag and electronic equipment |
| CN111191151B (en) * | 2019-12-20 | 2023-08-25 | 上海淇玥信息技术有限公司 | Method and device for pushing information based on POI (point of interest) tag and electronic equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2013091302A1 (en) | 2013-06-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102385636A (en) | Intelligent searching method and device | |
| CN107391706B (en) | Urban tourism question-answering system based on mobile internet | |
| US20140229102A1 (en) | Method and system for dynamic travel plan management | |
| US8880559B2 (en) | Location activity search engine computer system | |
| CN105761175A (en) | Tour route customization method and server | |
| US11049199B2 (en) | Contextual trip itinerary generator | |
| EP3579168A1 (en) | Information processing device, information processing method, and program | |
| JP2007219655A (en) | Facility information management system, facility information management method and facility information management program | |
| CN107943810A (en) | The construction method of building information map | |
| CN107257362A (en) | With time attention rate is in map Dynamic Announce event and brings chat method and system together | |
| CN114240528A (en) | Interactive scenic spot guide system for rural tourism | |
| CN112084401A (en) | Tour route customizing device and method | |
| CN202475755U (en) | Intelligent travel service system based on GIS | |
| CN105678383A (en) | Mobile knowledge service system on the basis of ontology model | |
| CN107270907A (en) | Tourist attraction information sharing method, route planning method and information sharing system | |
| US20160146608A1 (en) | Automatic tour guiding method | |
| Sasaki et al. | A study on the development of tourist support system using ICT and psychological effects | |
| WO2015065719A1 (en) | Computerized systems and methods for identifying a character string for a point of interest | |
| Zhan et al. | Minority tourist information service and sustainable development of tourism under the background of smart city | |
| Zeng et al. | Active recommendation of tourist attractions based on visitors interests and semantic relatedness | |
| Kulakov et al. | Ontological model of multi-source smart space content for use in cultural heritage trip planning | |
| Ependi et al. | Model for Mobile Application Development on Traveling Guide: A General Proposal | |
| Cao et al. | Integrating open data and generating travel itinerary in semantic-aware tourist information system | |
| Yin et al. | Design of the smart scenic spot service platform | |
| Luz et al. | Tourism mobile and recommendation systems-a state of the art |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C12 | Rejection of a patent application after its publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20120321 |