CN104156897B - Indoor guide system based on context aware - Google Patents
Indoor guide system based on context aware Download PDFInfo
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- CN104156897B CN104156897B CN201410360032.2A CN201410360032A CN104156897B CN 104156897 B CN104156897 B CN 104156897B CN 201410360032 A CN201410360032 A CN 201410360032A CN 104156897 B CN104156897 B CN 104156897B
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Abstract
The invention discloses a kind of indoor guide systems based on context aware,Including mobile phone terminal and server,The server end includes context aware subsystem,Recommend subsystem and navigation subsystem three parts,The public database of three subsystems,On the one hand context aware subsystem is responsible for acquisition user context information and provides location-based message push service,On the other hand,By bottom context information through the storage of processing extraction high layer information in the database,As the data source for recommending subsystem,Commending system can call corresponding proposed algorithm according to user's specific situation,Recommendation results are pushed to mobile phone terminal again,Recommendation results can also be as the route planning foundation of navigation subsystem,Navigation subsystem is using the showpiece in user's stroke list as the necessary place of route,Route planning is carried out in conjunction with user's specific situation,Finally,Best route is pushed to mobile phone terminal.
Description
Technical field
The invention belongs to internet of things field, are related to a kind of indoor guide system based on context aware.
Background technology
Based on being transmitted different from internet with information, Internet of Things is not only transmitted comprising information, Intelligent Information Processing and fusion
And one of key character of Internet of Things, it is through entire " object object is connected " of Internet of Things acquisition, control, transmission and upper layer application
Process.With the rapid development of computer and sensor technology, spread all over the computing resource of environment so that context aware is easily achieved.
Context aware as Internet of Things Intelligent Information Processing most critical can accomplish in the case where user does not send service request certainly
It is main to determine when to provide and which kind of service is provided.Context aware technology simplifies the interaction of user and network, improves user
Experience, therefore extensive concern has been obtained, context aware technology is also dissolved into the every aspect in life by each field scholar,
Middle tourist industry is considered most development potentiality.
Since Intelligent mobile equipment becomes increasingly popular, mobile commending system has universality and personalized two kinds of characteristics, at present
One of research hotspot of commending system research field is become.External many universities and research institution expand depth to mobile recommendation
Enter research.
With the development of tourist industry, individual traveler's " personalization " self-service trip by as the Developing mainstream of following tourist market, according to
" ctrip.com " the last time questionnaire survey shows that 84.3% tourist represents to go on a journey in a manner of self-service trip.It was travelling
Cheng Zhong, independent tourists, often more than team tourist, therefore, meet trip whenever and wherever possible to the demand of information and related tourist service
The demand of passerby provides quick convenient information for traveller, will become an important topic.
The popularity rate of smart mobile phone is higher and higher in recent years, Network Traffic Monitoring mechanism comScore issues
《ComScore2010 movement year summaries》In, the smart mobile phone utilization rate of US and European has respectively reached 27% and 31%.
Meanwhile Global Satellite Navigation System is rapidly developed, global positioning system, the GLONASS systems of Russia after the U.S., Europe
After " Galileo " plan that alliance exits, Chinese Beidou satellite navigation and positioning system is also evolving.In this context,
Some mobile travel services using mobile phone as platform are had logged out both at home and abroad.
The current many problems of travel information generally existing are mainly reflected in two aspects：One is the absence of personalization, existing
Tourism Information System seldom or give no thought to the preference of individual subscriber, recommend the user of different identity and different interest
All it is same content, and the special Audio Guide at each sight spot substantially using radio-frequency transmissions base station is laid, uses now
The Audio Guide of customization, special object is special and function is single, it is difficult to upgrade.Two are the absence of compliance, and existing Tourism Information System is basic
All it is unalterable seldom variation for considering external environment, for example is pushed away according to venue air quality or crowded degree for tourist
Recommend more comfortable tour.
If can know the personal preference and local environment of traveller in real time in tourism process, pass through context aware
The information for constantly obtaining user location, surrounding population and things and these things are calculated with the variable condition of time, then
Effective service immediately can be provided to the user according to user behavior and local environment.
The content of the invention
It is an object of the invention to overcome above-mentioned technology there are the defects of, a kind of indoor guide to visitors based on context aware is provided
System, the system make full use of existing resource to improve reception of visitor level and Service Quality using the smart mobile phone of tourist as platform
Amount, realizes automatic briefing when passenger goes sight-seeing showpiece indoors, and individual's customization tour excavates the potential interest of tourist in real time
Like and recommend possible interested showpiece, more personalized intelligent Service is provided for tourist.Its specific technical solution is：
A kind of indoor guide system based on context aware, including mobile phone terminal and server, the server end includes feelings
Scape perceives subsystem, recommends subsystem and navigation subsystem three parts, the public database of three subsystems, context aware
On the one hand system is responsible for acquisition user context information and provides location-based message push service, on the other hand, by bottom scene
Information through processing extraction high layer information storage in the database, as recommend subsystem data source, commending system can according to
Family specific situation calls corresponding proposed algorithm, then recommendation results are pushed to mobile phone terminal, and recommendation results can also be used as navigation subsystem
The route planning foundation of system, navigation subsystem is using the showpiece in user's stroke list as the necessary place of route, in conjunction with user
Specific situation carries out route planning, finally, best route is pushed to mobile phone terminal：
Database：The details of responsible storage article, user's history behavioral data, the cartographic information in place, place are each
Region density of stream of people information；
Context aware subsystem：It is responsible for obtaining the context information of user, context information includes the position of user herein, at one's side
Number, the residence time by a certain article, the personal like of user, be also responsible for flutterring immediately catch user interest variation, continue
Provide individual service to the user；
Recommend subsystem：Item lists are recommended for user according to user's history behavioral data and individual subscriber hobby；
Navigation subsystem：Sequence is integrated by the recommendation item lists that subsystem will be recommended to be formed, one is selected for user
Optimal tour, in navigation process, if context aware subsystem finds that the interest of user changes, the module meeting
According to user interest and current location dynamic adjustment tour.
Preferably, the context aware subsystem is also provided with a kind of location-based message push service, the service base
In user current location, whether user is judged in viewing showpiece, and which part showpiece what is watched is, then pushes the detailed of the showpiece
Thin information including text message and voice messaging, realizes MMS (Multimedia Message Service).
Preferably, the location-based message push process sees below step：
1) mobile phone end software timing is to the location information of server report of user；
2) after server receives location information, with map match in database, neighbouring Item Information is found；
3) compare user current location and the distance between each article nearby, find nearest Item Information；
4) Item Information found in 3) is pushed to mobile phone end.
Preferably, the recommendation process for recommending subsystem sees below step：
1) user interest models
Collaborative filtering realizes the modeling of user interest using user-project rating matrix, and individual consumer is all have been commented
The scoring that divided data collectively forms the user with non-score data is vectorial, and the scoring vector of all users presses row structure jointly in system
Into user-project rating matrix；For with m user, the Collaborative Recommendation system of n project, user-project scoring square
Battle array；
User obtains the scoring of project by display or implicit collection mode；
2) similarity calculating method
3) nearest-neighbors collection is sought
Nearest-neighbors collection is chosen using the method that the neighbours of fixed quantity collect；Neighbours are set in the present system collects size as 5,
Choose 5 neighbor nodes with designated user 1 or 1 similarity of article minimum；
4) recommendation list is formed
3) the article formation that the nearest-neighbors obtained in concentrate each neighbours interested and designated user 1 did not went sight-seeing is pushed away
Recommend list.
Preferably, the course of work step of the navigation subsystem is as follows：
1) user current location is determined；
2) site map is obtained, inquiry obtains the people in the specific location of each article and place Zhong Ge regions in recommendation list
Current density；
3) according to user current location, the article in recommendation list is arranged according to user current location apart from size
Sequence：The position of the near article in position in the list is forward, forms article recommendation list；
4) tour hommization is planned using A* algorithms and according to the density of stream of people in each region, ultimately forms route seat
Mark, and be sent on user's smart mobile phone.
Compared with prior art, beneficial effects of the present invention are：The present invention is fully sharp using the smart mobile phone of tourist as platform
Reception of visitor level and service quality are improved with existing resource, realizes automatic briefing when passenger goes sight-seeing showpiece indoors, it is private
People customizes tour, excavates the potential hobby of tourist in real time and recommends possible interested showpiece, is provided more for tourist
Add personalized intelligent Service.
Description of the drawings
Fig. 1 is the structure chart of the indoor guide system based on context aware；
Fig. 2 is the work flow 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.
Specific embodiment
Technical scheme is described in more detail in the following with reference to the drawings and specific embodiments.
A kind of overall framework of the indoor guide system based on context aware of the present invention is as shown in Figure 1：
The function description of each component：
Database：The details of responsible storage article, user's history behavioral data, the cartographic information in place, place are each
Region density of stream of people information.
Context aware subsystem：It is responsible for obtaining the context information of user, context information includes the position of user herein, at one's side
Number, the residence time by a certain article, the personal like of user.The module, which is also responsible for flutterring immediately, catches user interest variation
(passing through residence time of the user by a certain article), continues to provide individual service to the user.
Recommend subsystem：The module recommends columns of items according to user's history behavioral data and individual subscriber hobby for user
Table.
Navigation subsystem：The module is selected by the way that the recommendation item lists that subsystem is formed will be recommended to integrate sequence for user
Select an optimal tour.It, should if context aware subsystem finds that the interest of user changes in navigation process
Module can be according to user interest and current location dynamic adjustment tour.
Its detailed process is as shown in Figure 2：
A kind of each module of the indoor guide system based on context aware of the present invention is described in detail as follows：
Context aware subsystem：
1. context aware is how a kind of computing model optimized using the context information aid decision in environment is, it is necessary to solve
Certainly the problem of is mainly：Context information gathers and context information processing.Subsystem is designed using three-decker, scene acquisition layer master
Realize the real-time acquisition of context information, scene process layer is responsible for classifying context information, is used using dependency rule reasoning
Family model and interest model update, treated context information scene expression layer be converted into systematic learning to one know
Know, which is subjected to reasonable representation storage in the database, this scene knowledge can be as the number of other subsystems
According to source.According to different occasions, the context information that system is collected is also different.Detailed design is as shown in Figure 3.
2. context aware subsystem is also provided with a kind of location-based message push service, it is current which is based on user
Position, judges whether user is watching showpiece, and the details for being which part showpiece, then pushing the showpiece watched, bag
Text message and voice messaging are included, realizes MMS (Multimedia Message Service).
Location-based message push process sees below step：
1. mobile phone end software timing is to the location information of server report of user；
After 2. server receives location information, with map match in database, find neighbouring Item Information；
3. comparing user current location and the distance between each article nearby, nearest Item Information is found.
4. the Item Information found in 3 is pushed to mobile phone end.
Recommend subsystem
Subsystem is recommended to be intended to the current location information of the user interest and user that obtain using context aware to do for user
Go out personalized recommendation.
Subsystem is recommended to be embodied as using using the mixing proposed algorithm of collaborative filtering and content-based recommendation algorithm
Family personalized recommendation.
Recommendation process sees below step：
1. user interest models
Collaborative filtering realizes the modeling of user interest using user-project rating matrix, and individual consumer is all have been commented
The scoring that divided data collectively forms the user with non-score data is vectorial, and the scoring vector of all users presses row structure jointly in system
Into user-project rating matrix.For with m user, the Collaborative Recommendation system of n project, user-project rating matrix
R(m*n).As shown in Figure 4.
User can obtain the scoring of project by display or implicit collection mode,
2. similarity calculating method
The neighbor user for determining target user is a key point of collaborative filtering, and dominant systems generally pass through specific phase
The measurement of correlation between user is realized like degree computational methods, the system uses measurement of the Pearson correlation coefficients as similarity
Standard.
Skin in similarity (Pearson correlation-based similarity) based on Pearson correlation
Ademilson related coefficient has reacted the linearly related degree between two variables, its value is between [- 1,1].When two variables
Linear relationship enhancing when, related coefficient tends to 1 or -1；When a variable increase, when another variable also increases, show them
Between be it is positively related, related coefficient be more than 0；If the increase of variable, another variable but reduce, show be between them
Negatively correlated, related coefficient is less than 0；If related coefficient is equal to 0, show that there is no linear relationships between them.
3. seek nearest-neighbors collection
As shown in figure 5, the system using fixed quantity neighbours collection (K-neighborhoods neighborhoods,
KNN method) chooses nearest-neighbors collection.Neighbours are set in the present system and collect size as 5, that is, are chosen and designated user 1 or article 1
5 neighbor nodes of similarity minimum.It is noted here that the system, which can be changed flexibly, changes K values to adapt to different demands
Recommendation service.
4. form recommendation list
The article formation that the nearest-neighbors obtained in 3 concentrate each neighbours interested and designated user 1 did not went sight-seeing is pushed away
Recommend list.
Information filtering
By content-based recommendation algorithm, recommendation list will be obtained in 4 and carries out information filtering, forms consequently recommended row
Table is pushed to user terminal and navigation subsystem.
Navigation subsystem
It is that user forms tour that navigation subsystem, which is intended to using the recommendation list that subsystem sends over is recommended, and most
Client is shown to eventually.
Its process steps is as follows：
1. determine user current location；
2. obtaining site map, inquiry obtains the people in the specific location of each article and place Zhong Ge regions in recommendation list
Current density；
3. according to user current location, the article in recommendation list is arranged according to user current location apart from size
Sequence：The position of the near article in position in the list is forward, forms article recommendation list.
4. being planned using A* algorithms and according to the density of stream of people in each region tour hommization, route seat is ultimately formed
Mark, and be sent on user's smart mobile phone.
The system is mainly the guide to visitors of tourist quarters-room area.It is also worth noting that route planning is not once
Property, but it is dynamic.As user in navigation process before a certain not recommended article the residence time is longer, smart mobile phone
Terminal grasps user interest and changes with regard to that can flutter, and user interest will be submitted to context aware subsystem by mobile phone terminal at this time
System forms new recommended route so as to perform the guide to visitors process in Fig. 2 again for user.
The foregoing is only a preferred embodiment of the present invention, protection scope of the present invention is without being limited thereto, it is any ripe
Those skilled in the art are known in the technical scope of present disclosure, the letter for the technical solution that can be become apparent to
Altered or equivalence replacement are each fallen in protection scope of the present invention.
Claims (1)
1. a kind of indoor guide system based on context aware, which is characterized in that including mobile phone terminal and server, the server
End includes context aware subsystem, recommends subsystem and navigation subsystem three parts, the public database of three subsystems, feelings
Scape perceives subsystem and is on the one hand responsible for the location-based message push service of acquisition user context information offer, on the other hand, will
Bottom context information in the database, as the data source for recommending subsystem, recommends subsystem through the storage of processing extraction high layer information
System can call corresponding proposed algorithm according to user's specific situation, then recommendation results are pushed to mobile phone terminal, and recommendation results can also be made
For the route planning foundation of navigation subsystem, navigation subsystem using the showpiece in user's stroke list as the necessary place of route,
Route planning is carried out in conjunction with user's specific situation, finally, best route is pushed to mobile phone terminal：
Database：It is responsible for the details of storage article, user's history behavioral data, the cartographic information in place, each region in place
Density of stream of people information；
Context aware subsystem：It is responsible for obtaining the context information of user, context information includes the position of user herein, people at one's side
Number, the residence time by a certain article, the personal like of user are also responsible for flutterring immediately and catch user interest variation, continue as using
Family provides individual service；
Recommend subsystem：Item lists are recommended for user according to user's history behavioral data and individual subscriber hobby；
Navigation subsystem：Sequence is integrated by the recommendation item lists that subsystem will be recommended to be formed, it is optimal for user's selection one
Tour, in navigation process, if context aware subsystem find user interest change, navigation subsystem meeting
According to user interest and current location dynamic adjustment tour；
The context aware subsystem is also provided with a kind of location-based message push service, which is based on user's present bit
It puts, judges whether user is watching showpiece, and the details for being which part showpiece, then pushing the showpiece watched, including
Text message and voice messaging realize MMS (Multimedia Message Service)；
The location-based message push process sees below step：
1) mobile phone end software timing is to the location information of server report of user；
2) after server receives location information, with map match in database, neighbouring Item Information is found；
3) compare user current location and the distance between each article nearby, find nearest Item Information；
4) Item Information found in 3) is pushed to mobile phone end；
The recommendation process for recommending subsystem sees below step：
1) user interest models
Collaborative filtering realizes the modeling of user interest, all numbers that scored of individual consumer using user-project rating matrix
According to the scoring vector that the user is collectively formed with non-score data, in system, the scoring vector of all users is formed jointly by row uses
Family-project rating matrix；For with m user, the Collaborative Recommendation system of n project, user-project rating matrix；
User obtains the scoring of project by display or implicit collection mode；
2) similarity calculating method
3) nearest-neighbors collection is sought
Nearest-neighbors collection is chosen using the method that the neighbours of fixed quantity collect；Neighbours are set in the present system and collect size as 5, that is, are selected
Take 5 neighbor nodes with designated user 1 or 1 similarity of article minimum；
4) recommendation list is formed
3) article that the nearest-neighbors obtained in concentrate each neighbours interested and designated user 1 did not went sight-seeing is formed and recommends row
Table；
The course of work step of the navigation subsystem is as follows：
1) user current location is determined；
2) site map is obtained, it is close that inquiry obtains the stream of people in the specific location of each article and place Zhong Ge regions in recommendation list
Degree；
3) according to user current location, the article in recommendation list is ranked up according to user current location apart from size：
The position of the near article in position in the list is forward, forms article recommendation list；
4) tour hommization is planned using A* algorithms and according to the density of stream of people in each region, ultimately forms route coordinates,
And it is sent on user's smart mobile phone.
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| 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 |
| 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 |
| CN105589975B (en) * | 2016-02-05 | 2018-04-24 | 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 |
| CN109218049B (en) | 2017-06-30 | 2021-10-26 | 华为技术有限公司 | Control method, related equipment and system |
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