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Recommendations Based on Overlapping Communities for Location Based Social Networks (LBSNs)
English

Kavita G. Gare, Nilesh V. Alone
2015 International Journal of Innovative Research in Computer and Communication Engineering  
Based on the user check-in traces at venues and user/venue attributes, a coclustering framework is used to discover the overlapping communities of LBSNs users.  ...  Today, Location Based Social Networks(LBSNs) have become a rapidly growing area which attracts millions of people towards itself. LBSN sites are Foursquare, Bright kite, Gowalla, City Sense etc.  ...  I would like to take this opportunity to express my deep sense of gratitude towards him, for his invaluable guidance in completion of this project.  ... 
doi:10.15680/ijircce.2015.0306015 fatcat:x2p2cqbycjfxlklpxy6mklravu

When and Where?: Behavior Dominant Location Forecasting with Micro-Blog Streams

Bhaskar Gautam, Annappa Basava, Abhishek Singh, Amit Agrawal
2018 2018 IEEE International Conference on Data Mining Workshops (ICDMW)  
Our proposed algorithm is based on the dynamic formation of collective personality communities using different languages, opinions, geographical and temporal distributions for finding out optimized equivalent  ...  In this paper, we provide a novel algorithm to exploit the dynamic fluctuations in user's point-of-interest while forecasting the future place of visit with fine granularity.  ...  This feature-rich dimensions available on the social media and location-based social network motivate us to exploit fluctuating behavior of user towards long-range recommendation.  ... 
doi:10.1109/icdmw.2018.00169 dblp:conf/icdm/GautamBSA18 fatcat:dtbuei4b6rcu5o235b33tnqrse

A Novel Approach to Trust based Identification of Leaders in Social Networks

Pallab Dutta, A. Kumaravel
2016 Indian Journal of Science and Technology  
The characteristics of social networks play a very important role towards behavioralmodeling of a trust network based Recommender System (RS).  ...  Recommender Systems has been a research hotspot in recent times as an efficient information filtering tool, to filter out useful required information from ever expanding web.  ...  This analysis is required in many applications. The characteristics of social network plays a very important role towards behavioral modeling a trust network based Recommender System (RS).  ... 
doi:10.17485/ijst/2016/v9i10/85317 fatcat:y4ekjpdl7vemzba7s7bkmqfvim

IntRank: Interaction Ranking-Based Trustworthy Friend Recommendation

Lizi Zhang, Hui Fang, Wee Keong Ng, Jie Zhang
2011 2011IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications  
Social networks are fundamental to virtual communities (e.g., forums, blogs) and virtual communities benefit from well-established social networks.  ...  Towards this goal, we first formulate hypotheses on factors that influence trust and the probability of establishing friendships from various interaction attributes in virtual communities.  ...  Researchers in the graph mining area have applied link prediction for social networks to recommend friends in virtual communities.  ... 
doi:10.1109/trustcom.2011.36 dblp:conf/trustcom/ZhangFNZ11 fatcat:h5j4mwufwjd63ngmhtwnohrwbe

A Social Matching System for an Online Dating Network: A Preliminary Study

Richi Nayak, Meng Zhang, Lin Chen
2010 2010 IEEE International Conference on Data Mining Workshops  
This paper proposes a social matching system that uses past relations and user similarities in finding potential matches.  ...  users in the network.  ...  CONCLUSION Adoption of recommendation techniques in social networks for recommending people to people is currently gaining importance in the data mining community.  ... 
doi:10.1109/icdmw.2010.36 dblp:conf/icdm/NayakZC10 fatcat:5y42pq5aojh6fgdqpfnjxgdnbu

From Social Network to Semantic Social Network in Recommender System [article]

Khaled Sellami, Mohamed Ahmed-Nacer, Pierre Tiako
2015 arXiv   pre-print
In this paper, we propose a novel approach for recommendation systems called semantic social recommendation systems that enhance the analysis of social networks exploiting the power of semantic social  ...  Generally, these recommender systems are classified in three categories: content based, collaborative filtering, and hybrid based recommendation systems.  ...  FOAF has the potential to become an important tool in managing communities, and can be very useful to provide assistance to new entrants in a community, to find people with similar interests or to gather  ... 
arXiv:1407.3392v2 fatcat:2evt5vfppned5fmgrhz5vdtl4e

Towards Psychometrics-Based Friend Recommendations in Social Networking Services

Felix Beierle, Kai Grunert, Sebastian Gondor, Viktor Schluter
2017 2017 IEEE International Conference on AI & Mobile Services (AIMS)  
Social Networking Services are used to connect to known people as well as to discover new contacts. Current friend recommendation mechanisms typically utilize the social graph.  ...  In this paper, we argue that psychometrics, the field of measuring personality traits, can help make meaningful friend recommendations based on an extended social profile containing collected smartphone  ...  Yin et al. analyzed links in social networks based on "intuition-based" aspects: homophily (shared attributes), rarity (matching uncommon attributes), social influence (more likely to link to person that  ... 
doi:10.1109/aims.2017.22 dblp:conf/services/BeierleGGS17 fatcat:wkqiz6w6yjerbn2ul7ipftfn74

Survey on Matching Of Users in Social Networks Using Friend Book

Ms. D.Saral Jeeva Jothi, Ms.R. Ramyadevi
2017 International Journal Of Engineering And Computer Science  
Social Networking services focuses towards suggesting friends based on Users Social Graph or Geolocation based, which does not take user"s liking, disliking etc.  ...  In this survey paper we aims to address the identical user identification problem and recommending friends based on lifestyle of the users in social networking sites (SNS).  ...  Social Networking services focuses towards suggesting you friends based on Users Social Graph or Geo-location based, which neither take users life style into account nor user"s interest liking, disliking  ... 
doi:10.18535/ijecs/v6i2.10 fatcat:jc4dxf5bvfewzaaxcd5d7wvfm4

Modeling Influence with Semantics in Social Networks: a Survey [article]

Gerasimos Razis, Ioannis Anagnostopoulos, Sherali Zeadally
2018 arXiv   pre-print
In recent years, Online Social Networks (OSNs) have been established as a basic means of communication and often influencers and opinion makers promote politics, events, brands or products through viral  ...  The discovery of influential entities in all kinds of networks (e.g. social, digital, or computer) has always been an important field of study.  ...  Apart from discovering influential users, the topological and structural attributes of the networks can be used towards context-based identification of users' interests and similarities.  ... 
arXiv:1801.09961v3 fatcat:mnwvsphxgjdcvlu6vsn6g6pv5e

Survey on a Trust-Aware System for Personalized User Recommendations in Social Networks
IJARCCE - Computer and Communication Engineering

Supriya S, Saravanan D
2015 IJARCCE  
Multimedia recommendation system recommends video based on the user behavior which reduces network overhead and speed up the recommendation process.  ...  Trust is an important part in a social network from security point of view. Online video sharing systems is the most popular and provide features that allow users to post a video in a web page.  ...  Based on the user interests and report of the media content in the system,a collaborative filtering recommendation is used for video recommendation.A computing platform distributed in large-scale data  ... 
doi:10.17148/ijarcce.2015.4365 fatcat:uvmu3k3z2nf6vjfboaoqfe3wje

An Integrated Model for User Attribute Discovery: A Case Study on Political Affiliation Identification [chapter]

Swapna Gottipati, Minghui Qiu, Liu Yang, Feida Zhu, Jing Jiang
2014 Lecture Notes in Computer Science  
Discovering user demographic attributes from social media is a problem of considerable interest. The problem setting can be generalized to include three components -users, topics and behaviors.  ...  In recent studies on this problem, however, the behavior between users and topics are not effectively incorporated.  ...  Topic-independent social behavior is an important component used in several studies for prediction, recommendation and community detection tasks.  ... 
doi:10.1007/978-3-319-06608-0_36 fatcat:o6xkausj3fg5ngwq2mkimbjpna

Reciprocal Recommendation System for Online Dating

Peng Xia, Benyuan Liu, Yizhou Sun, Cindy Chen
2015 Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015 - ASONAM '15  
who are mutually interested in and likely to communicate with each other.  ...  In particular, males tend to be focused on their own interest and oblivious towards their attractiveness to potential dates, while females are more conscientious to their own attractiveness to the other  ...  A LDAbased method is employed in [13] to discover communities in Twitter-style online social networks, and matrix factorization are applied on each community to provide recommendations.  ... 
doi:10.1145/2808797.2809282 dblp:conf/asunam/XiaLSC15 fatcat:7jyhba54fnb7decnniar3rzoji

Privacy-Preserving Profile Matching System for Trust-Aware Personalized User Recommendations in Social Networks [chapter]

Vaishnavi Kulkarni, Archana S. Vaidya
2016 Advances in Intelligent Systems and Computing  
In the proposed system, a framework is introduced for handling trust in social networks, which is based on reputation mechanism.  ...  Trust is not perfectly transitive in social networks, in that trust decays along the transition path, but it is generally agreed that it can be communicated between people.  ...  Recently, it has gained a lot of interest with the advent of Web 2.0 and the enormous increase in the use of social networking applications, customer review sites, blogs, wikis, etc.  ... 
doi:10.1007/978-981-10-1675-2_4 fatcat:egzljzbgubgxbfsf7clrj3dc4u

A Survey on Personalized Service Recommendation Systems

Devdatta Godbole, Manish Narnaware
2016 International Journal of Engineering Research and  
Content-based filtering approaches use a series of different attributes of an item in order to recommend more product items having similar set of properties associated with them.  ...  Such a model is then used to predict items that the user may be interested in.  ...  ACKNOWLEDGMENT We express our sincere thanks to all the authors, whose papers or algorithms are published in the area of Recommendation Systems, Big data and Machine Learning in various conference proceedings  ... 
doi:10.17577/ijertv5is020595 fatcat:milrmhxx6rbwrcoyglx7zpsnfu

Reciprocal Recommendation System for Online Dating [article]

Peng Xia, Benyuan Liu, Yizhou Sun, Cindy Chen
2015 arXiv   pre-print
who are mutually interested in and likely to communicate with each other.  ...  In particular, males tend to be focused on their own interest and oblivious towards their attractiveness to potential dates, while females are more conscientious to their own attractiveness to the other  ...  A LDA-based method is employed in [12] to discover communities in Twitter-style online social networks, and matrix factorization are applied on each community to provide recommendations.  ... 
arXiv:1501.06247v2 fatcat:7s7nwv4cvjf6fi2i2pm6slpvze
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