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ANALYSIS OF LEARNING FRAMEWORK FOR PERSONALIZED DIVERSIFICATION
2020
International Journal of Advanced Trends in Computer Science and Engineering
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This proposed approach also addresses the problem personalised diversification of search results to beautify both diversification and personalization performances. ...
Search result diversification has received attention as a method to tackle query ambiguity. ...
In this approach, getting to know framework for express result diversification wherein subtopics are explicitly modeled. ...
doi:10.30534/ijatcse/2020/216952020
fatcat:cykotvtvarhczmsjij2erfrjzy
Explicit Query Interpretation and Diversification for Context-Driven Concept Search Across Ontologies
[chapter]
2016
Lecture Notes in Computer Science
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of a query; and (3) balances the relevance and diversity of search results. ...
In this paper, we propose a keyword-based concept search framework, which (1) exploits the structure and semantics in ontologies, by constructing contexts for each concept; (2) generates the interpretations ...
Paul Alexander of Stanford University for sharing the BioPortal query log. We would like to thank Prof. Gong Cheng for his advice and guidance on working with Falcons. ...
doi:10.1007/978-3-319-46523-4_17
fatcat:ix37tkjh4ncdtfygcul6vxa2ky
Diversifying contextual suggestions from location-based social networks
2014
Proceedings of the 5th Information Interaction in Context Symposium on - IIiX '14
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Therefore, we adapt web search result diversification approaches to the task of contextual suggestion. ...
The results also give insights on the effectiveness of our approach with different types of users. ...
In this section, we describe how we adapt a state-of-the-art approach for web search result diversification to the contextual suggestion problem. ...
doi:10.1145/2637002.2637018
dblp:conf/iiix/AlbakourDMO14
fatcat:cgyz6zpmcba6xn6rjg6a2ramjm
Structural Learning of Diverse Ranking
[article]
2015
arXiv
pre-print
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Compared with traditional methods, the advantages of our approach lie in that: (1) Directly optimizing DCEM as the loss function is more fundamental for the task; (2) Our framework does not rely on explicit ...
Relevance and diversity are both crucial criteria for an effective search system. In this paper, we propose a unified learning framework for simultaneously optimizing both relevance and diversity. ...
We use it as a basic supervised baseline. • SVMDIV. SVMDIV is a representative supervised approach for search result diversification [36] . ...
arXiv:1504.04596v2
fatcat:n2amn3mcljcnbh2pwce6sre3zm
Search Result Diversification
2015
Foundations and Trends in Information Retrieval
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Summary In this chapter, we have surveyed implicit approaches for search result diversification. ...
Explicit approaches have been shown to consistently outperform implicit ones in a standard web search result diversification scenario. ...
doi:10.1561/1500000040
fatcat:g4vxxda6u5aaljeqg6n47lushu
Intent-aware search result diversification
2011
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information - SIGIR '11
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Search result diversification has gained momentum as a way to tackle ambiguous queries. ...
In this paper, we propose to diversify the results retrieved for a given query, by learning the appropriateness of different retrieval models for each of the aspects underlying this query. ...
In particular, these two approaches represent the state-of-theart in explicit search result diversification. ...
doi:10.1145/2009916.2009997
dblp:conf/sigir/SantosMO11
fatcat:4yfoupua3rby7dnn2ytwck5kwi
Explicit web search result diversification
2012
SIGIR Forum
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To allow a thorough investigation of the role of novelty for search result diversification, in the next section, we adapt two existing novelty-based approaches to leverage explicit query aspect representations ...
In order to formalise this view, we propose a probabilistic objective for search result diversification, which is at the core of the Explicit Query Aspect Diversification (xQuAD) framework introduced in ...
Probability models for information retrieval based on Divergence From Randomness. Efficient computation of diverse query results. In Proceedings of the 24th Inter- ...
doi:10.1145/2492189.2492205
fatcat:g3f4j6r6ivhtzbm6mfi2zigsm4
Explicit Diversification of Event Aspects for Temporal Summarization
2018
ACM Transactions on Information Systems
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In this article, we propose a framework for the diversification of snippets using explicit event aspects, building upon recent works in search result diversification. ...
Through experimentation over the TREC TS 2013, 2014 and 2015 datasets, we show that explicit diversification for temporal summarization significantly outperforms classical noveltybased diversification, ...
Approaches to search result diversification can be divided into two main types, namely implicit or explicit [36] . ...
doi:10.1145/3158671
fatcat:fw4hyf2j5fccpldlgpfzq4bnra
Selectively diversifying web search results
2010
Proceedings of the 19th ACM international conference on Information and knowledge management - CIKM '10
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Search result diversification is a natural approach for tackling ambiguous queries. ...
A more lenient or more aggressive diversification strategy is typically encoded by existing approaches as a trade-off between promoting relevance or diversity in the search results. ...
CONCLUSIONS In this paper, we have introduced a novel selective approach for search result diversification. ...
doi:10.1145/1871437.1871586
dblp:conf/cikm/SantosMO10
fatcat:7wnlagil5jf2jmwvc7d5gcpqoi
Revisiting the cluster-based paradigm for implicit search result diversification
2018
Information Processing & Management
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2018) Revisiting the cluster-based paradigm for implicit search result diversification. ...
Abstract To cope with ambiguous and/or underspecified queries, search result diversification (SRD) is a key technique that has attracted a lot of attention. ...
However, there are some major challenges when deploying either the explicit methods or the supervised approaches for search result diversification. ...
doi:10.1016/j.ipm.2018.03.003
fatcat:hq5ln4f3kfhrvjr735quvvrnnq
Compact Aspect Embedding for Diversified Query Expansions
2014
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
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data sets, and show that our method significantly outperforms the state-of-the-art search result diversification approaches. ...
Recently they have experimentally demonstrate their effectiveness for the task of search result diversification. One challenge faced by existing DQE approaches is how to ensure the aspect coverage. ...
First, we are interested in mapping search results into the same aspect vector space and performing search results diversification directly in the vector space. ...
doi:10.1609/aaai.v28i1.8719
fatcat:ai5uwg3zgnfwpijx3rjaewu7ny
KDEIM at NTCIR-12 IMine-2 Search Intent Mining Task: Query Understanding through Diversified Ranking of Subtopics
2016
NTCIR Conference on Evaluation of Information Access Technologies
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We propose a method that extracts subtopics by leveraging the query suggestions from search engines. ...
To diversify the subtopics, we employ maximum marginal relevance (MMR) framework based diversification technique by balancing the relevance and novelty. ...
For example, the results of query "flower" now may contain image results and encyclopedia results as well as usual Web search results. We refer to such "types" of search results as verticals. ...
dblp:conf/ntcir/UllahSA16
fatcat:2kdz5biiwjfb5iawyzqgitxpau
ADAPTIVE LEARNING SEARCH, A NEW TOOL TO HELP COMPREHENDING METAHEURISTICS
2007
International journal on artificial intelligence tools
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We present a synthesis of some metaheuristics and their functioning seen under this angle, called Adaptive Learning Search. ...
We discuss how to design metaheuristics following this approach, and propose an implementation with our Open Metaheuristics framework, along with concrete examples. ...
Initialize a sample; Iterate until stopping criteria: Sampling: either explicit, implicit or direct, Learning: the algorithm extracts information from the sample, Diversification: it searches for new solutions ...
doi:10.1142/s0218213007003370
fatcat:zmhfzs6sjvgpbmvxcail6nu24i
Fusion helps diversification
2014
Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval - SIGIR '14
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A popular strategy for search result diversification is to first retrieve a set of documents utilizing a standard retrieval method and then rerank the results. ...
We take the output of a set of rankers, optimized for diversity or not, and find that data fusion can significantly improve state-of-the art diversification methods. ...
of each topic for search result diversification. ...
doi:10.1145/2600428.2609561
dblp:conf/sigir/LiangRR14
fatcat:5huypgvdlrcbngrfr3b7siimhi
GDESA: Greedy Diversity Encoder with Self-Attention for Search Results Diversification
2022
ACM Transactions on Information Systems
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Search result diversification aims to generate diversified search results so as to meet the various information needs of users. ...
In this paper, we propose a new supervised diversification framework as an ensemble of global interaction and document selection. ...
Existing models of search result diversiication can be categorized into supervised and unsupervised, depending on whether supervised learning is applied. ...
doi:10.1145/3544103
fatcat:ftsy3jv3qnhjjmmga36ffggbvu
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