Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
The use of MMR, diversity-based reranking for reordering documents and producing summaries
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Modern Information Retrieval
Beyond independent relevance: methods and evaluation metrics for subtopic retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The Journal of Machine Learning Research
Formal models for expert finding in enterprise corpora
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
LDA-based document models for ad-hoc retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Predicting diverse subsets using structural SVMs
Proceedings of the 25th international conference on Machine learning
ArnetMiner: extraction and mining of academic social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the Second ACM International Conference on Web Search and Data Mining
A Topic Modeling Approach and Its Integration into the Random Walk Framework for Academic Search
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Learning to Rank for Information Retrieval
Foundations and Trends in Information Retrieval
Redundancy, diversity and interdependent document relevance
ACM SIGIR Forum
Suggesting friends using the implicit social graph
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
A Combination Approach to Web User Profiling
ACM Transactions on Knowledge Discovery from Data (TKDD)
Topic-level social network search
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Diversified ranking on large graphs: an optimization viewpoint
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Foundations and Trends in Information Retrieval
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Expert finding is concerned about finding persons who are knowledgeable on a given topic. It has many applications in enterprise search, social networks, and collaborative management. In this paper, we study the problem of diversification for expert finding. Specifically, employing an academic social network as the basis for our experiments, we aim to answer the following question: Given a query and an academic social network, how to diversify the ranking list, so that it captures the whole spectrum of relevant authors' expertise? We precisely define the problem and propose a new objective function by incorporating topic-based diversity into the relevance ranking measurement. A learning-based model is presented to solve the objective function. Our empirical study in a real system validates the effectiveness of the proposed method, which can achieve significant improvements (+15.3%-+94.6% by MAP) over alternative methods.