CN104156897A - Indoor exhibition guiding system based on circumstance perception - Google Patents
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Abstract
The invention discloses an indoor exhibition guiding system based on circumstance perception. The indoor exhibition guiding system comprises a mobile phone end and a server, wherein the server end comprises three parts, namely a circumstance perception subsystem, a recommend subsystem and a navigation subsystem; the three subsystems share a database; the circumstance perception subsystem is responsible for acquiring user circumstance information, providing location-based message pushing service, extracting higher level information from bottom layer circumstance information through processing, and storing the higher level information into the database to be used as a data source of the recommend subsystem, so that the recommend system can call corresponding recommend algorithm according to user's particular circumstance and then push the recommend result to the mobile phone end; the recommend result can also be used as basis for path planning of the navigation subsystem; the navigation subsystem chooses the exhibit in the journey list of the user as a place must be passed in the path, the path planning is conducted according to the particular circumstance of the user, and finally, the optimum path is pushed to the mobile phone end.
Description
Technical field
The invention belongs to technology of Internet of things field, relate to a kind of indoor guide system based on context aware.
Background technology
Be different from internet taking communication as main, not only inclusion information transmission of Internet of Things, Intelligent Information Processing and to merge be also one of key character of Internet of Things, it runs through whole " thing thing is connected " process of Internet of Things collection, control, transmission and upper layer application.Along with developing rapidly of computing machine and sensor technology, the computational resource that spreads all over environment makes context aware be easy to realize.Can accomplish as the context aware of Internet of Things Intelligent Information Processing most critical which kind of service when autonomous judgement provide and provide in the situation that user does not send services request.Context aware technology has been simplified the mutual of user and network, has promoted user's experience, has therefore obtained paying close attention to widely, and each field scholar is also dissolved into the every aspect in life by context aware technology, and wherein tourist industry is considered to tool development potentiality.
Because Intelligent mobile equipment is day by day universal, mobile commending system has universality and personalized two specific characters, has become one of study hotspot of commending system research field at present.External many universities and research institution have launched further investigation to mobile recommendation.
Along with the development of tourist industry, individual traveler's " personalization " self-service trip will become the Developing mainstream of following tourist market, shows according to " ctrip.com " the last survey, and 84.3% tourist represents to go on a journey in the mode of self-service trip.In tourism process, independent tourists often more than the visitor of team, therefore, meets tourist's demand whenever and wherever possible to the demand of information and relevant tourist service, for tourist provides fast information easily, will become an important topic.
The popularity rate of smart mobile phone is more and more higher in recent years, and in " comScore2010 moves a year summary " that the comScore of Network Traffic Monitoring mechanism issues, the smart mobile phone utilization rate of US and European has reached respectively 27% and 31%.Meanwhile, GPS (Global Position System) is developed rapidly, and after " Galileo " plan of exiting continue the GPS of the U.S., Muscovite GLONASS system, European Union, the Beidou satellite navigation and positioning system of China is also at development.Under such background, some mobile travel services taking mobile phone as platform are exited both at home and abroad.
The current a lot of problems of travel information ubiquity, be mainly reflected in two aspects: the one, lack personalization, existing Tourism Information System seldom or give no thought to the preference of individual subscriber, the user who recommends different identity and different interest is same content, and the special Audio Guide used of present each sight spot adopts substantially is to lay radio-frequency transmissions base station, adopt the Audio Guide of customization, specially special the and function singleness of thing, is difficult to upgrading.The 2nd, lack compliance, existing Tourism Information System is substantially all the variation of unalterable little consideration external environment condition, such as being that visitor recommends comparatively comfortable tour according to venue air quality or crowded degree.
If the individual preference of knowing tourist and environment of living in that can be real-time in tourism process, calculate the information of constantly obtaining customer location, surrounding population and things by context aware, and these things are along with the variable condition of time, so just can effectively serve for user provides instant according to user behavior and environment of living in.
Summary of the invention
The object of the invention is to overcome the defect that above-mentioned technology exists, a kind of indoor guide system based on context aware is provided, this system is taking visitor's smart mobile phone as platform, make full use of existing resource and improve reception of visitor level and service quality, automatic briefing in the time that the indoor passenger of realization goes sight-seeing showpiece, private customization tour, excavates in real time the potential hobby of visitor and recommends the interested showpiece of possibility, for visitor provides more personalized Intelligent Service.Its concrete technical scheme is:
A kind of indoor guide system based on context aware, comprise mobile phone terminal and server, described server end comprises context aware subsystem, recommend subsystem and navigation subsystem three parts, database of three sub-system share, context aware subsystem is responsible on the one hand gathering user context information location-based message push service is provided, on the other hand, treated bottom context information extraction high layer information is stored in database, as the data source of recommending subsystem, commending system can call corresponding proposed algorithm according to user's specific situation, again recommendation results is pushed to mobile phone terminal, recommendation results also can be served as the route planning foundation of navigation subsystem, navigation subsystem must be through place as route using the showpiece in the list of user's stroke, carry out route planning in conjunction with user's specific situation again, finally, best route is pushed to mobile phone terminal:
Database: be responsible for the details of stores, user's historical behavior data, the cartographic information in place, each region, place stream of people's density information;
Context aware subsystem: be responsible for obtaining user's context information, context information comprises user's position herein, number at one's side, in the residence time on a certain article side, user's personal like, is also responsible for immediately flutterring and catches user interest variation, continues as user individual service is provided;
Recommend subsystem: recommend item lists according to user's historical behavior data and individual subscriber hobby for user;
Navigation subsystem: by the recommendation item lists of recommending subsystem to form is integrated to sequence, for user selects a best tour, in navigation process, if context aware subsystem discovery user's interest changes, this module can dynamically be adjusted tour according to user interest and current location.
Preferably, described context aware subsystem also provides with the location-based message push service of one, this service is based on user's current location, judge whether user is watching showpiece, and which part showpiece what watch is, then push the details of this showpiece, comprise text message and voice messaging, realize MMS (Multimedia Message Service).
Preferably, described location-based message push process is shown in lower step:
1) smart mobile phone end software timing is to the positional information of server report of user;
2) server is received after positional information, with map match in database, and near the Item Information finding;
3) compare the distance between user's current location and near each article, find nearest Item Information;
4) by 3) in the Item Information that finds be pushed to smart mobile phone end.
Preferably, the recommendation process of described recommendation subsystem is shown in lower step:
1) user interest modeling
Collaborative filtering adopts user-project rating matrix to realize the modeling of user interest, the all score data of individual consumer and not score data form this user's scoring vector jointly, and in system, all users' scoring vector is common by row formation user-project rating matrix; For thering is m user, the Collaborative Recommendation system of n project, its user-project rating matrix;
User obtains by demonstration or implicit expression collection mode the scoring of project;
2) similarity calculating method
3) ask nearest-neighbors collection
Adopt the method for neighbours' collection of fixed qty to choose nearest-neighbors collection; In native system, setting neighbours, to collect size be 5, chooses 5 neighbor nodes with designated user 1 or article 1 similarity minimum;
4) form recommendation list
By 3) in the nearest-neighbors that obtains concentrate the article that each neighbours are interested and designated user 1 was not gone sight-seeing to form recommendation list.
Preferably, the course of work step of described navigation subsystem is as follows:
1) determine user's current location;
2) obtain place map, inquiry obtains the particular location of each article in recommendation list and people's current density in Zhong Ge region, place;
3) according to user's current location, by the article in recommendation list according to sorting apart from size with user's current location: the position of the near article in position in this list is forward, forms article recommendation list;
4) adopt A* algorithm and according to people's current density in each region, tour hommization planned, finally forming route coordinate, and send on user's smart mobile phone.
Compared with prior art, beneficial effect of the present invention is: the present invention is taking visitor's smart mobile phone as platform, make full use of existing resource and improve reception of visitor level and service quality, automatic briefing in the time that the indoor passenger of realization goes sight-seeing showpiece, private customization tour, excavate in real time the potential hobby of visitor and recommend the interested showpiece of possibility, for visitor provides more personalized Intelligent Service.
Brief description of the drawings
Fig. 1 is the structural drawing of the indoor guide system based on context aware;
Fig. 2 is the workflow diagram of the indoor guide system based on context aware;
Fig. 3 is context aware subsystem architecture figure;
Fig. 4 is user-project rating matrix;
Fig. 5 is nearest-neighbors set algorithm schematic diagram.
Embodiment
Below in conjunction with the drawings and specific embodiments, technical scheme of the present invention is described in more detail.
The overall framework of a kind of indoor guide system based on context aware of the present invention is as shown in Figure 1:
The functional description of each ingredient:
Database: be responsible for the details of stores, user's historical behavior data, the cartographic information in place, each region, place stream of people's density information.
Context aware subsystem: be responsible for obtaining user's context information, context information comprises user's position herein, number at one's side, the residence time on a certain article side, user's personal like.This module is also responsible for immediately flutterring and is caught user interest variation (residence time by user on a certain article side), continues as user individual service is provided.
Recommend subsystem: this module is recommended item lists according to user's historical behavior data and individual subscriber hobby for user.
Navigation subsystem: this module is by the recommendation item lists of recommending subsystem to form is integrated to sequence, for user selects a best tour.In navigation process, if finding user's interest, context aware subsystem changes, this module can dynamically be adjusted tour according to user interest and current location.
Its detailed process is as shown in Figure 2:
Each module of a kind of indoor guide system based on context aware of the present invention is described in detail as follows:
Context aware subsystem:
1. context aware is a kind of computation schema that how to utilize the context information aid decision making in environment to optimize, and needs the problem of solution mainly: context information collection and context information processing.Subsystem adopts three-decker design, sight acquisition layer is mainly realized the Real-time Obtaining of context information, sight processing layer is responsible for context information to classify, user model is carried out in the reasoning of application dependency rule and interest model upgrades, treated context information is converted at sight presentation layer the knowledge that systematic learning arrives, this sight knowledge is carried out to reasonable representation and be stored in database, this sight knowledge can be used as the data source of other subsystems.According to different occasions, the context information of systematic collection is also different.Detailed design as shown in Figure 3.
2. context aware subsystem also provides with the location-based message push service of one, this service is based on user's current location, judge whether user is watching showpiece, and which part showpiece what watch is, then push the details of this showpiece, comprise text message and voice messaging, realize MMS (Multimedia Message Service).
Location-based message push process is shown in lower step:
1. smart mobile phone end software timing is to the positional information of server report of user;
2. server is received after positional information, with map match in database, and near the Item Information finding;
3. compare the distance between user's current location and near each article, find nearest Item Information.
4. the Item Information finding in 3 is pushed to smart mobile phone end.
Recommend subsystem
Recommend subsystem to be intended to the user interest and the current positional information recommendation personalized for user makes of user that utilize context aware to obtain.
Recommend subsystem to adopt the mixing proposed algorithm of collaborative filtering and content-based proposed algorithm to be embodied as user-customized recommended.
Recommendation process is shown in lower step:
1. user interest modeling
Collaborative filtering adopts user-project rating matrix to realize the modeling of user interest, the all score data of individual consumer and not score data form this user's scoring vector jointly, and in system, all users' scoring vector is common by row formation user-project rating matrix.For thering is m user, the Collaborative Recommendation system of n project, its user-project rating matrix R (m*n).As shown in Figure 4.
User can obtain by demonstration or implicit expression collection mode the scoring of project,
2. similarity calculating method
The neighbor user of determining targeted customer is a key point of collaborative filtering, and main flow system generally realizes the tolerance of correlativity between user by specific similarity calculating method, and native system adopts the module of Pearson's related coefficient as similarity.
Pearson's related coefficient in similarity (Pearson correlation-based similarity) based on Pearson's correlativity has been reacted the linear dependence degree between two variablees, and its value is between [1,1].In the time that the linear relationship of two variablees strengthens, related coefficient is tending towards 1 or-1; When a variable increases, when another variable also increases, show between them it is positively related, related coefficient is greater than 0; If a variable increases, another variable but reduces, and shows between them it is negative correlation, and related coefficient is less than 0; If related coefficient equals 0, show not exist between them linear dependence relation.
3. ask nearest-neighbors collection
As shown in Figure 5, native system adopts the method for neighbours' collection (K-neighborhoods neighborhoods, KNN) of fixed qty to choose nearest-neighbors collection.In native system, setting neighbours, to collect size be 5, chooses 5 neighbor nodes with designated user 1 or article 1 similarity minimum.In this attention, native system can be revised flexibly and change the recommendation service that K value adapts to different demands.
4. form recommendation list
Concentrate the article that each neighbours are interested and designated user 1 was not gone sight-seeing to form recommendation list the nearest-neighbors obtaining in 3.
Information filtering
By content-based proposed algorithm, carry out information filtering by obtaining recommendation list in 4, form final recommendation list, be pushed to user terminal and navigation subsystem.
Navigation subsystem
Navigation subsystem is intended to utilize recommends the recommendation list that sends over of subsystem to form tour for user, and is finally shown to client.
Its process steps is as follows:
1. determine user's current location;
2. obtain place map, inquiry obtains the particular location of each article in recommendation list and people's current density in Zhong Ge region, place;
3. according to user's current location, by the article in recommendation list according to sorting apart from size with user's current location: the position of the near article in position in this list is forward, forms article recommendation list.
4. adopt A* algorithm and according to people's current density in each region, tour hommization planned, finally forming route coordinate, and send on user's smart mobile phone.
This system is mainly the guide to visitors of tourist quarters-room area.It should be noted that route planning is not disposable simultaneously, but dynamic.As user in navigation process before a certain not recommended article the residence time longer, intelligent mobile phone terminal just can be flutterred and grasp user interest and change, now mobile phone terminal will be submitted to user interest context aware subsystem, thereby the guide to visitors process again in execution graph 2 is that user forms new recommended route.
The above; it is only preferably embodiment of the present invention; protection scope of the present invention is not limited to this; any be familiar with those skilled in the art the present invention disclose technical scope in, the simple change of the technical scheme that can obtain apparently or equivalence replace all fall within the scope of protection of the present invention.
Claims (5)
1. the indoor guide system based on context aware, it is characterized in that, comprise mobile phone terminal and server, described server end comprises context aware subsystem, recommend subsystem and navigation subsystem three parts, database of three sub-system share, context aware subsystem is responsible on the one hand gathering user context information location-based message push service is provided, on the other hand, treated bottom context information extraction high layer information is stored in database, as the data source of recommending subsystem, commending system can call corresponding proposed algorithm according to user's specific situation, again recommendation results is pushed to mobile phone terminal, recommendation results also can be served as the route planning foundation of navigation subsystem, navigation subsystem must be through place as route using the showpiece in the list of user's stroke, carry out route planning in conjunction with user's specific situation again, finally, best route is pushed to mobile phone terminal:
Database: be responsible for the details of stores, user's historical behavior data, the cartographic information in place, each region, place stream of people's density information;
Context aware subsystem: be responsible for obtaining user's context information, context information comprises user's position herein, number at one's side, in the residence time on a certain article side, user's personal like, is also responsible for immediately flutterring and catches user interest variation, continues as user individual service is provided;
Recommend subsystem: recommend item lists according to user's historical behavior data and individual subscriber hobby for user;
Navigation subsystem: by the recommendation item lists of recommending subsystem to form is integrated to sequence, for user selects a best tour, in navigation process, if context aware subsystem discovery user's interest changes, this module can dynamically be adjusted tour according to user interest and current location.
2. the indoor guide system method based on context aware according to claim 1, it is characterized in that, described context aware subsystem also provides with the location-based message push service of one, this service is based on user's current location, judge whether user is watching showpiece, and which part showpiece what watch be, then push the details of this showpiece, comprise text message and voice messaging, realize MMS (Multimedia Message Service).
3. the indoor guide system method based on context aware according to claim 2, is characterized in that, described location-based message push process is shown in lower step:
1) smart mobile phone end software timing is to the positional information of server report of user;
2) server is received after positional information, with map match in database, and near the Item Information finding;
3) compare the distance between user's current location and near each article, find nearest Item Information;
4) by 3) in the Item Information that finds be pushed to smart mobile phone end.
4. the indoor guide system method based on context aware according to claim 1, is characterized in that, the recommendation process of described recommendation subsystem is shown in lower step:
1) user interest modeling
Collaborative filtering adopts user-project rating matrix to realize the modeling of user interest, the all score data of individual consumer and not score data form this user's scoring vector jointly, and in system, all users' scoring vector is common by row formation user-project rating matrix; For thering is m user, the Collaborative Recommendation system of n project, its user-project rating matrix;
User obtains by demonstration or implicit expression collection mode the scoring of project;
2) similarity calculating method
3) ask nearest-neighbors collection
Adopt the method for neighbours' collection of fixed qty to choose nearest-neighbors collection; In native system, setting neighbours, to collect size be 5, chooses 5 neighbor nodes with designated user 1 or article 1 similarity minimum;
4) form recommendation list
By 3) in the nearest-neighbors that obtains concentrate the article that each neighbours are interested and designated user 1 was not gone sight-seeing to form recommendation list.
5. the indoor guide system method based on context aware according to claim 1, is characterized in that, the course of work step of described navigation subsystem is as follows:
1) determine user's current location;
2) obtain place map, inquiry obtains the particular location of each article in recommendation list and people's current density in Zhong Ge region, place;
3) according to user's current location, by the article in recommendation list according to sorting apart from size with user's current location: the position of the near article in position in this list is forward, forms article recommendation list;
4) adopt A* algorithm and according to people's current density in each region, tour hommization planned, finally forming route coordinate, and send on user's smart mobile phone.
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Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104598537A (en) * | 2014-12-30 | 2015-05-06 | 小米科技有限责任公司 | Target object information recommendation method and device |
| CN105095987A (en) * | 2015-06-30 | 2015-11-25 | 北京奇虎科技有限公司 | Shopping navigation method, server for shopping navigation and client terminal |
| CN105139301A (en) * | 2015-08-13 | 2015-12-09 | 厦门维途信息技术有限公司 | Guiding method based on BP neural network |
| CN105278532A (en) * | 2015-11-04 | 2016-01-27 | 中国科学技术大学 | Personalized autonomous explanation method of guidance by robot tour guide |
| CN105447185A (en) * | 2015-12-15 | 2016-03-30 | 西安电子科技大学 | Knowledge and position based individualized scenic spots recommendation method |
| CN105589975A (en) * | 2016-02-05 | 2016-05-18 | 腾讯科技（深圳）有限公司 | Information recommendation method and device |
| CN106779288A (en) * | 2016-11-17 | 2017-05-31 | 哈尔滨工程大学 | A kind of ocean platform weight control system and control method based on computational intelligence |
| CN107391605A (en) * | 2017-06-30 | 2017-11-24 | 北京奇虎科技有限公司 | Information-pushing method, device and mobile terminal based on geographical position |
| CN109166225A (en) * | 2018-10-19 | 2019-01-08 | 沈洁 | A kind of intelligent multimedia guide system |
| CN109218049A (en) * | 2017-06-30 | 2019-01-15 | 华为技术有限公司 | A kind of control method, relevant device and system |
| CN110459203A (en) * | 2018-05-03 | 2019-11-15 | 百度在线网络技术（北京）有限公司 | A kind of intelligent sound guidance method, device, equipment and storage medium |
| CN110472139A (en) * | 2019-07-16 | 2019-11-19 | 浙江大学城市学院 | A kind of personalized recommendation based on context aware information and guide system and control method |
| WO2020220188A1 (en) * | 2019-04-29 | 2020-11-05 | Grabtaxi Holdings Pte. Ltd. | Communications server apparatus, methods and communications systems for recommending one or more points-of-interest for a transport-related service to a user |
| CN113680070A (en) * | 2021-08-26 | 2021-11-23 | 网易（杭州）网络有限公司 | Virtual interactive object browsing method and device, electronic equipment and storage medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102915518A (en) * | 2012-08-29 | 2013-02-06 | 太原理工大学 | Context-awareness system for smart campus services |
| CN103886484A (en) * | 2014-03-14 | 2014-06-25 | 河海大学常州校区 | Shopping guiding system for large-scale commercial block |
-
2014
- 2014-07-24 CN CN201410360032.2A patent/CN104156897B/en not_active Expired - Fee Related
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102915518A (en) * | 2012-08-29 | 2013-02-06 | 太原理工大学 | Context-awareness system for smart campus services |
| CN103886484A (en) * | 2014-03-14 | 2014-06-25 | 河海大学常州校区 | Shopping guiding system for large-scale commercial block |
Non-Patent Citations (2)
| Title |
|---|
| 李聪 等: ""电子商务协同过滤稀疏性研究：一个分类视角"", 《管理工程学报》 * |
| 杨青青 等: ""基于Windows Mobile的校园移动向导系统的设计"", 《中国教育信息化》 * |
Cited By (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104598537A (en) * | 2014-12-30 | 2015-05-06 | 小米科技有限责任公司 | Target object information recommendation method and device |
| CN105095987A (en) * | 2015-06-30 | 2015-11-25 | 北京奇虎科技有限公司 | Shopping navigation method, server for shopping navigation and client terminal |
| CN105139301A (en) * | 2015-08-13 | 2015-12-09 | 厦门维途信息技术有限公司 | Guiding method based on BP neural network |
| CN105139301B (en) * | 2015-08-13 | 2019-04-12 | 法信维途(厦门)信息技术有限公司 | A kind of guidance method based on BP neural network |
| CN105278532B (en) * | 2015-11-04 | 2018-09-07 | 中国科学技术大学 | Personalization machine people's tourist guide independently explains method |
| CN105278532A (en) * | 2015-11-04 | 2016-01-27 | 中国科学技术大学 | Personalized autonomous explanation method of guidance by robot tour guide |
| CN105447185A (en) * | 2015-12-15 | 2016-03-30 | 西安电子科技大学 | Knowledge and position based individualized scenic spots recommendation method |
| CN105447185B (en) * | 2015-12-15 | 2018-11-16 | 西安电子科技大学 | The personalized tourist attractions recommended method of knowledge based and position |
| CN105589975A (en) * | 2016-02-05 | 2016-05-18 | 腾讯科技（深圳）有限公司 | Information recommendation method and device |
| CN106779288A (en) * | 2016-11-17 | 2017-05-31 | 哈尔滨工程大学 | A kind of ocean platform weight control system and control method based on computational intelligence |
| CN109218049A (en) * | 2017-06-30 | 2019-01-15 | 华为技术有限公司 | A kind of control method, relevant device and system |
| CN107391605A (en) * | 2017-06-30 | 2017-11-24 | 北京奇虎科技有限公司 | Information-pushing method, device and mobile terminal based on geographical position |
| US11556100B2 (en) | 2017-06-30 | 2023-01-17 | Huawei Technologies Co., Ltd. | Control method, related device, and system |
| CN110459203A (en) * | 2018-05-03 | 2019-11-15 | 百度在线网络技术（北京）有限公司 | A kind of intelligent sound guidance method, device, equipment and storage medium |
| CN109166225A (en) * | 2018-10-19 | 2019-01-08 | 沈洁 | A kind of intelligent multimedia guide system |
| WO2020220188A1 (en) * | 2019-04-29 | 2020-11-05 | Grabtaxi Holdings Pte. Ltd. | Communications server apparatus, methods and communications systems for recommending one or more points-of-interest for a transport-related service to a user |
| CN110472139A (en) * | 2019-07-16 | 2019-11-19 | 浙江大学城市学院 | A kind of personalized recommendation based on context aware information and guide system and control method |
| CN113680070A (en) * | 2021-08-26 | 2021-11-23 | 网易（杭州）网络有限公司 | Virtual interactive object browsing method and device, electronic equipment and storage medium |
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