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
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Proceedings of the 11th international conference on World Wide Web
Novelty and redundancy detection in adaptive filtering
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Normalized Cuts and Image Segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
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
Improving recommendation lists through topic diversification
WWW '05 Proceedings of the 14th international conference on World Wide Web
Automatic evaluation of summaries using N-gram co-occurrence statistics
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Improving web search results using affinity graph
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Modeling word burstiness using the Dirichlet distribution
ICML '05 Proceedings of the 22nd international conference on Machine learning
Learning from labeled and unlabeled data on a directed graph
ICML '05 Proceedings of the 22nd international conference on Machine learning
A general optimization framework for smoothing language models on graph structures
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Novelty and diversity in information retrieval evaluation
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the Second ACM International Conference on Web Search and Data Mining
An axiomatic approach for result diversification
Proceedings of the 18th international conference on World wide web
LexRank: graph-based lexical centrality as salience in text summarization
Journal of Artificial Intelligence Research
Redundancy, diversity and interdependent document relevance
ACM SIGIR Forum
A unified framework for recommending diverse and relevant queries
Proceedings of the 20th international conference on World wide web
Identifying relevant social media content: leveraging information diversity and user cognition
Proceedings of the 22nd ACM conference on Hypertext and hypermedia
Learning from collective human behavior to introduce diversity in lexical choice
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Decayed DivRank: capturing relevance, diversity and prestige in information networks
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Diversity in ranking via resistive graph centers
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
Timeline generation through evolutionary trans-temporal summarization
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
New approaches to diversity and novelty in recommender systems
FDIA'11 Proceedings of the Fourth BCS-IRSG conference on Future Directions in Information Access
Diversity in ranking using negative reinforcement
Proceedings of the ACM SIGKDD Workshop on Mining Data Semantics
Proceedings of the VLDB Endowment
Tweet recommendation with graph co-ranking
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
AUSUM: approach for unsupervised bug report summarization
Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering
A picture paints a thousand words: a method of generating image-text timelines
Proceedings of the 21st ACM international conference on Information and knowledge management
Diversified recommendation on graphs: pitfalls, measures, and algorithms
Proceedings of the 22nd international conference on World Wide Web
Towards a personalized, scalable, and exploratory academic recommendation service
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Generating extractive summaries of scientific paradigms
Journal of Artificial Intelligence Research
Comments-oriented document summarization based on multi-aspect co-feedback ranking
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
Exploratory search with semantic transformations using collaborative knowledge bases
Proceedings of the 7th ACM international conference on Web search and data mining
Latent dirichlet allocation based diversified retrieval for e-commerce search
Proceedings of the 7th ACM international conference on Web search and data mining
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Information networks are widely used to characterize the relationships between data items such as text documents. Many important retrieval and mining tasks rely on ranking the data items based on their centrality or prestige in the network. Beyond prestige, diversity has been recognized as a crucial objective in ranking, aiming at providing a non-redundant and high coverage piece of information in the top ranked results. Nevertheless, existing network-based ranking approaches either disregard the concern of diversity, or handle it with non-optimized heuristics, usually based on greedy vertex selection. We propose a novel ranking algorithm, DivRank, based on a reinforced random walk in an information network. This model automatically balances the prestige and the diversity of the top ranked vertices in a principled way. DivRank not only has a clear optimization explanation, but also well connects to classical models in mathematics and network science. We evaluate DivRank using empirical experiments on three different networks as well as a text summarization task. DivRank outperforms existing network-based ranking methods in terms of enhancing diversity in prestige.