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Recommendations Based on Overlapping Communities for Location Based Social Networks (LBSNs)
English
2015
International Journal of Innovative Research in Computer and Communication Engineering
English
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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
2018
2018 IEEE International Conference on Data Mining Workshops (ICDMW)
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2018 pre-print arXiv:1812.06443v1 fatcat:5e5hqrtnmrdg7m33qeabt6lli4
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
2016
Indian Journal of Science and Technology
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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
2011
2011IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications
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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
2010
2010 IEEE International Conference on Data Mining Workshops
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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]
2015
arXiv
pre-print
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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
2017
2017 IEEE International Conference on AI & Mobile Services (AIMS)
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2017 pre-print arXiv:1705.10512v1 fatcat:wt653dkt6nbmnjkqlnsrehwvoeOther Versions
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
2017
International Journal Of Engineering And Computer Science
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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]
2018
arXiv
pre-print
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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
2015
IJARCCE
IJARCCE - Computer and Communication Engineering
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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]
2014
Lecture Notes in Computer Science
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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
2015
Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015 - ASONAM '15
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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]
2016
Advances in Intelligent Systems and Computing
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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
2016
International Journal of Engineering Research and
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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]
2015
arXiv
pre-print
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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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