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BoostFM
2017
Proceedings of the 22nd International Conference on Intelligent User Interfaces - IUI '17
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To address this problem, with both implicit feedback and feature information, we propose a feature-based collaborative boosting recommender called BoostFM, which integrates boosting into factorization ...
Specifically, BoostFM is an adaptive boosting framework that linearly combines multiple homogeneous component recommenders, which are repeatedly constructed on the basis of the individual FM model by a ...
This work was also partially supported by the National Natural Science Foundation of China (No. 61472073). ...
doi:10.1145/3025171.3025211
dblp:conf/iui/YuanGJCYZ17
fatcat:n7mh6wxf4bgszjh2fesfsaoi6y
Context sensitive stemming for web search
2007
Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '07
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Traditionally, stemming has been applied to Information Retrieval tasks by transforming words in documents to the their root form before indexing, and applying a similar transformation to query terms. ...
by average Discounted Cumulative Gain (DCG5) by 6.1% on these queries and 1.8% over all query traffic. ...
However uniform weighting is not going to work and a query dependent weighting is still a challenging unsolved problem [20] . ...
doi:10.1145/1277741.1277851
dblp:conf/sigir/PengALL07
fatcat:ybyapr3mdbggrf6soguzwnztnm
Adaptive image retrieval using a Graph model for semantic feature integration
2006
Proceedings of the 8th ACM international workshop on Multimedia information retrieval - MIR '06
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Moreover, to further improve effectiveness, the retrieval model should ideally incorporate context-dependent feature representations to allow for retrieval on a higher semantic level. ...
However, the plethora of data poses a challenge in terms of feature selection and integration for effective retrieval. ...
The research leading to this paper was supported by the European Commission under contract FP6-027026, Knowledge Space of semantic inference for automatic annotation and retrieval of multimedia content-K-Space ...
doi:10.1145/1178677.1178696
dblp:conf/mir/UrbanJ06
fatcat:xnuwqg567zgrdldtqolutfw6qa
Supporting Analysts by Dynamic Extraction and Classification of Requirements-Related Knowledge
2019
2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)
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co(occurrence) in a corpus [40] and will assign different weights to terms depending on the context they occur in. ...
Thus, the extraction would be treated as finding all common terms which appear in relevant contexts and our algorithm identifies the relevance of terms by computing the intersection between the two hierarchical ...
doi:10.1109/icse.2019.00057
dblp:conf/icse/AbadGZF19
fatcat:ki2ioor325an3cnarzpuxkqs7y
A Fixed-Point Method for Weighting Terms in Verbose Informational Queries
2014
Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management - CIKM '14
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The term weighting and document ranking functions used with informational queries are typically optimized for cases in which queries are short and documents are long. ...
distinct query terms is a useful heuristic. ...
Acknowledgments This research was supported in part by DARPA contract HR0011-12-C-0015 and NSF award 1065250. ...
doi:10.1145/2661829.2661957
dblp:conf/cikm/PaikO14
fatcat:uyzxtwksujhpth4xg7qwpw4lom
An approach based on Combination of Features for automatic news retrieval
[article]
2020
arXiv
pre-print
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Along with introducing this new approach, we proposed a dataset by identifying the most commonly used keywords in documents and using the most appropriate documents to help them with the abundance of vocabulary ...
Although the conceptual relationship between documents may be negligible, it is important to provide useful information and relevant content to users. ...
For this purpose they computed distinct vector space model from document collections by pre-processing step such as stemming, term weighting based on TF-IDF and reduction of the amount of terms based on ...
arXiv:2004.11699v1
fatcat:vppybnsh4rdixiqz3vrdsf2iva
Contextual Ranking of Keywords Using Click Data
2009
Proceedings / International Conference on Data Engineering
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We then define a new feature space to represent the interestingness of concepts, and describe a new approach to estimate their relevancy for a given context. ...
All these applications can potentially benefit from a successful solution as it enables computational efficiency (by decreasing the input size), noise reduction, or overall improved user satisfaction. ...
who helped developing and building the Contextual Shortcuts platform. ...
doi:10.1109/icde.2009.76
dblp:conf/icde/IrmakBK09
fatcat:6gtfi6er5rhnxctcvpduiwoxx4
Optimal Query Expansion Based on Hybrid Group Mean Enhanced Chimp Optimization Using Iterative Deep Learning
2022
Electronics
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The internet is surrounded by uncertain information which necessitates the usage of natural language processing and soft computing techniques to extract the relevant documents. ...
Moreover, the proposed optimal query expansion technique has shown a substantial improvement in terms of a normalized discounted cumulative gain of 0.87, a mean average precision of 0.35, and a mean reciprocal ...
Informed Consent Statement: Not applicable. ...
doi:10.3390/electronics11101556
fatcat:53iznxcukza3hor65ycm6py2tu
Learning to Rewrite Queries
2016
Proceedings of the 25th ACM International on Conference on Information and Knowledge Management - CIKM '16
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It is widely known that there exists a semantic gap between web documents and user queries and bridging this gap is crucial to advance information retrieval systems. ...
The candidate generating phase provides us the flexibility to reuse most of existing query rewriters; while the candidate ranking phase allows us to explicitly optimize search relevance. ...
DCG has been widely used to assess relevance in the context of search engines [13] . ...
doi:10.1145/2983323.2983835
dblp:conf/cikm/HeTOKYC16
fatcat:nwvlype7yvcvhcat6guccu274i
Click-boosting random walk for image search reranking
2013
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service - ICIMCS '13
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A new algorithm, named Clickboosting Random Walk, is proposed. The algorithm utilizes clicked images to locate similar images that are not clicked, and reranks them by random walk. ...
A fundamental issue underlying the success of existing image reranking approaches is the ability in identifying potentially useful recurrent patterns or relevant training examples from the initial search ...
The second term a j is the score of image j obtained by click-boosting. ω is a weighting parameter which linearly weights the above two terms, and ω ∈ [0, 1]. ...
doi:10.1145/2499788.2499810
dblp:conf/icimcs/YangZYZN13
fatcat:4khgavq4vfgf5mmmzc63omotji
A Big Data Semantic Driven Context Aware Recommendation Method for Question-Answer Items
2019
IEEE Access
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Content-Based recommender systems (CB) filter relevant items to users in overloaded search spaces using information about their preferences. ...
INDEX TERMS Content-based recommender system, context-awareness, user profile contextualization, map-reduce, big data. • A suitable way to study status updates, i.e. a userprovided free text, in the QA ...
NDCG at first depends on the Discounted Cumulative Gain (DCG), which premise is that highly relevant documents appearing lower in a search result list should be penalized as the graded relevance value ...
doi:10.1109/access.2019.2957881
fatcat:cb7bzwqxjfemllvvwnqdsmzur4
Supervised reranking for web image search
2010
Proceedings of the international conference on Multimedia - MM '10
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In this paper, 11 lightweight reranking features are proposed by representing the textual query using visual context and pseudo relevant images from the initial search result. ...
In other words, a query-independent reranking model will be learned for all queries using query-dependent reranking features. ...
the log function is motivated by the discount term in NDCG (Normalized Discounted Cumulative Gain) [12] , which assigns a larger importance to top images in the returned result since their relevance ...
doi:10.1145/1873951.1873977
dblp:conf/mm/YangH10
fatcat:r2dcmmqmtvffpa6jouov76qzwa
Click-boosting multi-modality graph-based reranking for image search
2014
Multimedia Systems
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A new reranking algorithm, named clickboosting multi-modality graph-based reranking, is proposed. ...
Mining useful patterns without understanding query is risky, and may lead to incorrect judgment in reranking. ...
Introduction The emergence of Web 2.0 has brought a new era of information production. ...
doi:10.1007/s00530-014-0379-8
fatcat:thyd5lxa5zbl7jygne26ke3wam
Personalized Context-Aware Point of Interest Recommendation
[article]
2018
arXiv
pre-print
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Moreover, we present different scores calculated from multiple LBSNs and show how we incorporate new information from the mapping into a POI recommendation approach. ...
Furthermore, we introduce a dataset on locations' contextual appropriateness and demonstrate its usefulness in predicting the contextual relevance of locations. ...
, it is essential to assist users to find relevant and useful information according to their needs and context. ...
arXiv:1806.05736v1
fatcat:lblylvjqpbh2vlppf55s5alssi
Context-Aware, adaptive information retrieval for investigative tasks
2007
Proceedings of the 12th international conference on Intelligent user interfaces - IUI '07
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In such a task, users must progressively search and analyze relevant information before drawing a conclusion. ...
Second, we develop a context-aware method that can adaptively retrieve and evaluate information relevant to an ongoing investigation. ...
ACKNOWLEDGEMENTS We would like to thank David Gotz for sharing his code on context model, and Bill Yoshimi for proofreading the paper. ...
doi:10.1145/1216295.1216321
dblp:conf/iui/WenZA07
fatcat:ikdvxplmova7tjapbze37c4gj4
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