SimFusion: measuring similarity using unified relationship matrix
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Ranking objects based on relationships
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Social networks, incentives, and search
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Latent semantic analysis for multiple-type interrelated data objects
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Optimizing web search using social annotations
Proceedings of the 16th international conference on World Wide Web
Can social bookmarking enhance search in the web?
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
iLink: search and routing in social networks
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient search ranking in social networks
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Shine: search heterogeneous interrelated entities
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Efficient top-k querying over social-tagging networks
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Finding a team of experts in social networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Social search and discovery using a unified approach
Proceedings of the 20th ACM conference on Hypertext and hypermedia
Intelligent menu planning: recommending set of recipes by ingredients
Proceedings of the ACM multimedia 2012 workshop on Multimedia for cooking and eating activities
| Hi-index | 0.00 |
In online social networking services, there are a range of scenarios in which users want to search a particular person given the targeted person one's name. The challenge of such people search is namesake, which means that there are many people possess the same names in the social network. In this paper, we propose to leverage the query contexts to tackle such problems. For example, given the information of one's graduation year and city, the last names of some individuals, one may wish to find classmates from his/her high school. We formulate such problem as the context-based people search. Given a social network in which each node is associated with a set of labels and given a query set of labels consisting of a targeted name label and other context labels, our goal is to return a ranking list of persons who possess the targeted name label and connects to other context labels with minimum communication costs through an effective subgraph in the social network. We consider the interactions among query labels to propose a grouping-based method to solve the context-based people search. Our method consists of three major parts. First, we model those nodes with query labels into a group graph which is able to reduce the search space to enhance the time efficiency. Second, we identify three different kinds of connectors which connecting different groups, and exploit connectors to find the corresponding detailed graph topology from the group graph. Third, we propose a Connector-Steiner Tree algorithm to retrieve a resulting ranked list of individuals who possess the targeted label. Experimental results on the DBLP bibliography data show that our grouping-based method can reach the good quality of returned persons as a greedy search algorithm at a considerable outperformance on the time efficiency.