Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
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
The budgeted maximum coverage problem
Information Processing Letters
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
Hierarchical document categorization with support vector machines
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Improving web search results using affinity graph
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Large Margin Methods for Structured and Interdependent Output Variables
The Journal of Machine Learning Research
Learning user preferences for sets of objects
ICML '06 Proceedings of the 23rd international conference on Machine learning
Less is more: probabilistic models for retrieving fewer relevant documents
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Robust classification of rare queries using web knowledge
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
A support vector method for optimizing average precision
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Training structural SVMs when exact inference is intractable
Proceedings of the 25th international conference on Machine learning
Learning diverse rankings with multi-armed bandits
Proceedings of the 25th international conference on Machine learning
Cutting-plane training of structural SVMs
Machine Learning
Enhancing diversity, coverage and balance for summarization through structure learning
Proceedings of the 18th international conference on World wide web
Interactively optimizing information retrieval systems as a dueling bandits problem
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Predicting structured objects with support vector machines
Communications of the ACM - Scratch Programming for All
Learning to Disambiguate Search Queries from Short Sessions
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Learning to Rank for Information Retrieval
Foundations and Trends in Information Retrieval
Learning optimal subsets with implicit user preferences
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Redundancy, diversity and interdependent document relevance
ACM SIGIR Forum
Probabilistic latent maximal marginal relevance
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Metrics for assessing sets of subtopics
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Learning to rank relevant and novel documents through user feedback
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Learning to generate summary as structured output
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Supervised reranking for web image search
Proceedings of the international conference on Multimedia
Detecting duplicate web documents using clickthrough data
Proceedings of the fourth ACM international conference on Web search and data mining
Proceedings of the fourth ACM international conference on Web search and data mining
Multi-dimensional search result diversification
Proceedings of the fourth ACM international conference on Web search and data mining
Towards a collection-based results diversification
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
Video summarization via transferrable structured learning
Proceedings of the 20th international conference on World wide web
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
Information Processing and Management: an International Journal
Structured learning of two-level dynamic rankings
Proceedings of the 20th ACM international conference on Information and knowledge management
Diverse retrieval via greedy optimization of expected 1-call@k in a latent subtopic relevance model
Proceedings of the 20th ACM international conference on Information and knowledge management
Max-Sum diversification, monotone submodular functions and dynamic updates
PODS '12 Proceedings of the 31st symposium on Principles of Database Systems
Extracting keyphrase set with high diversity and coverage using structural SVM
APWeb'12 Proceedings of the 14th Asia-Pacific international conference on Web Technologies and Applications
Approximating low-dimensional coverage problems
Proceedings of the twenty-eighth annual symposium on Computational geometry
Online learning to diversify from implicit feedback
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Playlist prediction via metric embedding
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning to diversify expert finding with subtopics
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Combining implicit and explicit topic representations for result diversification
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Large-margin learning of submodular summarization models
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
Coverage-based search result diversification
Information Retrieval
AUSUM: approach for unsupervised bug report summarization
Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering
Temporal corpus summarization using submodular word coverage
Proceedings of the 21st ACM international conference on Information and knowledge management
Measuring the coverage and redundancy of information search services on e-commerce platforms
Electronic Commerce Research and Applications
Diverse M-best solutions in markov random fields
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Toward whole-session relevance: exploring intrinsic diversity in web search
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Mining subtopics from different aspects for diversifying search results
Information Retrieval
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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In many retrieval tasks, one important goal involves retrieving a diverse set of results (e.g., documents covering a wide range of topics for a search query). First of all, this reduces redundancy, effectively showing more information with the presented results. Secondly, queries are often ambiguous at some level. For example, the query "Jaguar" can refer to many different topics (such as the car or feline). A set of documents with high topic diversity ensures that fewer users abandon the query because no results are relevant to them. Unlike existing approaches to learning retrieval functions, we present a method that explicitly trains to diversify results. In particular, we formulate the learning problem of predicting diverse subsets and derive a training method based on structural SVMs.