A study on two geometric location problems
Information Processing Letters
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
Finding subsets maximizing minimum structures
Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms
Approximation algorithms for dispersion problems
Journal of Algorithms
Facility Dispersion and Remote Subgraphs
SWAT '96 Proceedings of the 5th Scandinavian Workshop on Algorithm Theory
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
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
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
Learning diverse rankings with multi-armed bandits
Proceedings of the 25th international conference on Machine learning
Predicting diverse subsets using structural SVMs
Proceedings of the 25th international conference on Machine learning
On syntactic versus computational views of approximability
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
Proceedings of the Second ACM International Conference on Web Search and Data Mining
It takes variety to make a world: diversification in recommender systems
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
An axiomatic approach for result diversification
Proceedings of the 18th international conference on World wide web
Structured search result differentiation
Proceedings of the VLDB Endowment
Diversifying web search results
Proceedings of the 19th international conference on World wide web
DivQ: diversification for keyword search over structured databases
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Multi-document summarization via budgeted maximization of submodular functions
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
ACM SIGMOD Record
Approximation algorithms for diversified search ranking
ICALP'10 Proceedings of the 37th international colloquium conference on Automata, languages and programming: Part II
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
A class of submodular functions for document summarization
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
On query result diversification
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Incremental diversification for very large sets: a streaming-based approach
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Intent-aware search result diversification
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Approximation algorithms for maximum dispersion
Operations Research Letters
Maximizing a Monotone Submodular Function Subject to a Matroid Constraint
SIAM Journal on Computing
DisC diversity: result diversification based on dissimilarity and coverage
Proceedings of the VLDB Endowment
Top-k diversity queries over bounded regions
ACM Transactions on Database Systems (TODS)
Diversified top-k graph pattern matching
Proceedings of the VLDB Endowment
On the complexity of query result diversification
Proceedings of the VLDB Endowment
Hi-index | 0.00 |
Result diversification has many important applications in databases, operations research, information retrieval, and finance. In this paper, we study and extend a particular version of result diversification, known as max-sum diversification. More specifically, we consider the setting where we are given a set of elements in a metric space and a set valuation function f defined on every subset. For any given subset S, the overall objective is a linear combination of f(S) and the sum of the distances induced by S. The goal is to find a subset S satisfying some constraints that maximizes the overall objective. This problem is first studied by Gollapudi and Sharma in [17] for modular set functions and for sets satisfying a cardinality constraint (uniform matroids). In their paper, they give a 2-approximation algorithm by reducing to an earlier result in [20]. The first part of this paper considers an extension of the modular case to the monotone submodular case, for which the algorithm in [17] no longer applies. Interestingly, we are able to maintain the same 2-approximation using a natural, but different greedy algorithm. We then further extend the problem by considering any matroid constraint and show that a natural single swap local search algorithm provides a 2-approximation in this more general setting. This extends the Nemhauser, Wolsey and Fisher approximation result [20] for the problem of submodular function maximization subject to a matroid constraint (without the distance function component). The second part of the paper focuses on dynamic updates for the modular case. Suppose we have a good initial approximate solution and then there is a single weight-perturbation either on the valuation of an element or on the distance between two elements. Given that users expect some stability in the results they see, we ask how easy is it to maintain a good approximation without significantly changing the initial set. We measure this by the number of updates, where each update is a swap of a single element in the current solution with a single element outside the current solution. We show that we can maintain an approximation ratio of 3 by just a single update if the perturbation is not too large.