The small-world phenomenon: an algorithmic perspective
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
An Approach to Integrating Query Refinement in SQL
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
FALCON: Feedback Adaptive Loop for Content-Based Retrieval
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Efficient Query Refinement in Multimedia Databases
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Probabilistic information retrieval approach for ranking of database query results
ACM Transactions on Database Systems (TODS)
Matching resumes and jobs based on relevance models
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic ranking of database query results
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
An experimental comparison of click position-bias models
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
How does clickthrough data reflect retrieval quality?
Proceedings of the 17th ACM conference on Information and knowledge management
Multi-aspect expertise matching for review assignment
Proceedings of the 17th ACM conference on Information and knowledge management
A dynamic bayesian network click model for web search ranking
Proceedings of the 18th international conference on World wide web
Expected reciprocal rank for graded relevance
Proceedings of the 18th ACM conference on Information and knowledge management
Constrained multi-aspect expertise matching for committee review assignment
Proceedings of the 18th ACM conference on Information and knowledge management
A unified approach to ranking in probabilistic databases
Proceedings of the VLDB Endowment
It's not you, it's me: detecting flirting and its misperception in speed-dates
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Ranking in context-aware recommender systems
Proceedings of the 20th international conference companion on World wide web
Pseudo test collections for learning web search ranking functions
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Identifying similar people in professional social networks with discriminative probabilistic models
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Finding someone you will like and who won't reject you
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
Stochastic matching and collaborative filtering to recommend people to people
Proceedings of the fifth ACM conference on Recommender systems
Not just a wink and smile: an analysis of user-defined success in online dating
Proceedings of the 2012 iConference
Explicit and implicit user preferences in online dating
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
A common neighbour based two-way collaborative recommendation method
Proceedings of the 27th Annual ACM Symposium on Applied Computing
CCR: a content-collaborative reciprocal recommender for online dating
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
The effect of suspicious profiles on people recommenders
UMAP'12 Proceedings of the 20th international conference on User Modeling, Adaptation, and Personalization
MEET: a generalized framework for reciprocal recommender systems
Proceedings of the 21st ACM international conference on Information and knowledge management
iHR: an online recruiting system for Xiamen Talent Service Center
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Whom to mention: expand the diffusion of tweets by @ recommendation on micro-blogging systems
Proceedings of the 22nd international conference on World Wide Web
Proceedings of the 7th ACM conference on Recommender systems
Understanding and promoting micro-finance activities in Kiva.org
Proceedings of the 7th ACM international conference on Web search and data mining
User Modeling and User-Adapted Interaction
| Hi-index | 0.00 |
Match-making systems refer to systems where users want to meet other individuals to satisfy some underlying need. Examples of match-making systems include dating services, resume/job bulletin boards, community based question answering, and consumer-to-consumer marketplaces. One fundamental component of a match-making system is the retrieval and ranking of candidate matches for a given user. We present the first in-depth study of information retrieval approaches applied to match-making systems. Specifically, we focus on retrieval for a dating service. This domain offers several unique problems not found in traditional information retrieval tasks. These include two-sided relevance, very subjective relevance, extremely few relevant matches, and structured queries. We propose a machine learned ranking function that makes use of features extracted from the uniquely rich user profiles that consist of both structured and unstructured attributes. An extensive evaluation carried out using data gathered from a real online dating service shows the benefits of our proposed methodology with respect to traditional match-making baseline systems. Our analysis also provides deep insights into the aspects of match-making that are particularly important for producing highly relevant matches.