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Machine learned ranking of entity facets

Roelof van Zwol, Lluís Garcia Pueyo, Mridul Muralidharan, Börkur Sigurbjörnsson
2010 Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '10  
We introduce an approach for a machine learned ranking of entity facets based on user click feedback and features extracted from three different ranking sources.  ...  The objective of the learned model is to predict the click-through rate on an entity facet.  ...  To support the entity facet ranking application of Figure 1, we propose a machine learned ranking of entity facets based on user click feedback.  ... 
doi:10.1145/1835449.1835662 dblp:conf/sigir/ZwolPMS10 fatcat:34yjxikjrzdy3ibocmllpmhweu

Ranking related entities for web search queries

Changsung Kang, Srinivas Vadrevu, Ruiqiang Zhang, Roelof van Zwol, Lluis Garcia Pueyo, Nicolas Torzec, Jianzhang He, Yi Chang
2011 Proceedings of the 20th international conference companion on World wide web - WWW '11  
In this work, we present an extensive analysis of Web-scale entity ranking, based on machine learned ranking models using an ensemble of pairwise preference models.  ...  learning to rank framework.  ...  We cast the problem of entity ranking as a supervised machine learning problem with the goal of predicting the relevance of the related entity to the query entity.  ... 
doi:10.1145/1963192.1963227 dblp:conf/www/KangVZZPTHC11 fatcat:676nizdtufex5p5krpimjn5m3i

Learning to rank related entities in Web search

Changsung Kang, Dawei Yin, Ruiqiang Zhang, Nicolas Torzec, Jianzhang He, Yi Chang
2015 Neurocomputing  
In this work, we present an extensive analysis of Web-scale entity ranking, based on machine learned ranking models using an ensemble of pair-wise preference models.  ...  learning to rank framework.  ...  Machine-learned Ranking for Entities Machine learning has been extensively used for many ranking tasks (8) .  ... 
doi:10.1016/j.neucom.2015.04.004 fatcat:xmezq76o2fdd5efeygiixjis6i

Facet-based opinion retrieval from blogs

Olga Vechtomova
2010 Information Processing & Management  
The paper presents methods of retrieving blog posts containing opinions about an entity expressed in the query.  ...  Methods of structuring queries into facets, facet expansion using Wikipedia, and a facet-based retrieval are also investigated in this work.  ...  The objective of the task is to retrieve a ranked list of blog posts, which express opinions about the entity (entities) described in the topic. An example of the topic is given in Figure 1 .  ... 
doi:10.1016/j.ipm.2009.06.005 fatcat:fip3myunozhj3obgrnc2w5qvoe

Enhanced Automatically Mining Facets for Queries and Clustering with Side Information Model

V.Yasvanth kumaar, Dr.G. Singaravel
2018 IJARCCE  
The proposed system developing an application for recommendations of reports articles to the readers of a news portal.  ...  However, the relative importance of this side-information is also tough to estimate, particularly once a number of the data is noisy.  ...  One is known as entity ranking (given a query and target category, return a ranked list of relevant entities), another is list completion (given a query and example entities, return similar entities),  ... 
doi:10.17148/ijarcce.2018.71026 fatcat:o34i6s4yabcfhg5e6sj6izslaq

FacetGist

Tarique Siddiqui, Xiang Ren, Aditya Parameswaran, Jiawei Han
2016 Proceedings of the 25th ACM International on Conference on Information and Knowledge Management - CIKM '16  
Given a collection of technical documents, the goal of Facet Extraction is to automatically label each document with a set of concepts for the key facets (e.g., application, technique, evaluation metrics  ...  We then formulate a joint optimization problem, and propose an efficient algorithm for graph-based label propagation to estimate the facet of each concept mention.  ...  The views and conclusions contained in this document are those of the author(s) and should not be interpreted as representing the official policies of the U.S. Army Research Laboratory or the U.S.  ... 
doi:10.1145/2983323.2983828 pmid:28210517 pmcid:PMC5308212 dblp:conf/cikm/SiddiquiRPH16 fatcat:tc7vyaknbvdflbfh7ic3atii4a

Towards Deep and Representation Learning for Talent Search at LinkedIn [article]

Rohan Ramanath, Hakan Inan, Gungor Polatkan, Bo Hu, Qi Guo, Cagri Ozcaglar, Xianren Wu, Krishnaram Kenthapadi, Sahin Cem Geyik
2018 arXiv   pre-print
Our key contributions include: (i) Learning semantic representations of sparse entities within the talent search domain, such as recruiter ids, candidate ids, and skill entity ids, for which we utilize  ...  We also explore learning to rank approaches applied to deep models, and show the benefits for the talent search use case.  ...  The structured fields add sparsity to the feature space when used as a part of a machine learning ranking model.  ... 
arXiv:1809.06473v1 fatcat:tinmwa5li5bnnksmsn7x6hcmki

Gleaning Types for Literals in RDF Triples with Application to Entity Summarization [chapter]

Kalpa Gunaratna, Krishnaprasad Thirunarayan, Amit Sheth, Gong Cheng
2016 Lecture Notes in Computer Science  
Associating meaning with data in a machine-readable format is at the core of the Semantic Web vision, and typing is one such process.  ...  We show the usefulness of generated types by utilizing them to group facts on the basis of their semantics in computing diversified entity summaries by extending a state-of-the-art summarization algorithm  ...  Any opinions, findings, and conclusions/recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF.  ... 
doi:10.1007/978-3-319-34129-3_6 fatcat:lartcyze4bev5eprshyoab234e

SIGIR 2017 Workshop on eCommerce (ECOM17)

Jon Degenhardt, Surya Kallumadi, Maarten de Rijke, Luo Si, Andrew Trotman, Yinghui Xu
2017 Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval - SIGIR '17  
SIGIR has for several years seen sponsorship from these kinds of organisations, who clearly value the importance of research into Information Retrieval.  ...  eCommerce Information Retrieval has received little attention in the academic literature, yet it is an essential component of some of the largest web sites (such as eBay, Amazon, Airbnb, Alibaba, Taobao  ...  Research topics and challenges that are usually encountered in this domain include: • Machine learning techniques such as online learning and deep learning for eCommerce applications • Semantic representation  ... 
doi:10.1145/3077136.3084367 dblp:conf/sigir/DegenhardtKRSTX17 fatcat:nu5o6e576fe47jrt2ffl3qxnlq

Exploratory Analysis of Highly Heterogeneous Document Collections [article]

Arun S. Maiya, John P. Thompson, Francisco Loaiza-Lemos, Robert M. Rolfe
2013 arXiv   pre-print
Tagging strategies employed include both unsupervised and supervised approaches based on machine learning and natural language processing.  ...  Our system is based on intelligently tagging individual documents in a purely automated fashion and exploiting these tags in a powerful faceted browsing framework.  ...  on supervised machine learning (i.e., LinearSVM), unsupervised machine learning (i.e., latent Dirichlet allocation or LDA), and natural language processing (e.g., Named Entity Recognition or NER). • We  ... 
arXiv:1308.2359v1 fatcat:ueryp5vbcna4ngegw6jfcpki5a

Exploratory analysis of highly heterogeneous document collections

Arun S. Maiya, John P. Thompson, Francisco Loaiza-Lemos, Robert M. Rolfe
2013 Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '13  
Tagging strategies employed include both unsupervised and supervised approaches based on machine learning and natural language processing.  ...  Our system is based on intelligently tagging individual documents in a purely automated fashion and exploiting these tags in a powerful faceted browsing framework.  ...  on supervised machine learning (i.e., LinearSVM), unsupervised machine learning (i.e., latent Dirichlet allocation or LDA), and natural language processing (e.g., Named Entity Recognition or NER). • We  ... 
doi:10.1145/2487575.2488195 dblp:conf/kdd/MaiyaTLR13 fatcat:akai4h7acvbbbesqyk6pyi4yoy

Identifying Relevant Document Facets for Keyword-Based Search Queries [article]

Lanbo Zhang
2015 arXiv   pre-print
We propose a machine learning approach and a set of useful features, and evaluate our approach using a movie data set from INEX.  ...  In this paper, we study the problem of identifying document facet-value pairs that are relevant to a keyword-based search query.  ...  Secondly, we use a learning-based approach for FVP ranking.  ... 
arXiv:1501.00744v1 fatcat:56rd5cvsj5h57hexxrs5c6ufmu

Numerical Facet Range Partition: Evaluation Metric and Methods [article]

Xueqing Liu, Chengxiang Zhai, Wei Han, Onur Gungor
2017 arXiv   pre-print
Existing work has tried to optimize faceted systems in many aspects, but little work has been done on optimizing numerical facet ranges (e.g., price ranges of product).  ...  To enable quantitative evaluation of a partition algorithm, we propose an evaluation metric to be applied to search engine logs.  ...  Due to the heterogeneity of entity structures on the web, facets ranking can be classified as ranking facet [4] , ranking facet values [14] and ranking (facet, value) pairs [15] .  ... 
arXiv:1610.10000v3 fatcat:rxslcyvydzfe3msxn57leg4dfe

Numerical Facet Range Partition

Xueqing Liu, Chengxiang Zhai, Wei Han, Onur Gungor
2017 Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion  
Existing work has tried to optimize faceted systems in many aspects, but little work has been done on optimizing numerical facet ranges (e.g., price ranges of product).  ...  To enable quantitative evaluation of a partition algorithm, we propose an evaluation metric to be applied to search engine logs.  ...  Due to the heterogeneity of entity structures on the web, facets ranking can be classified as ranking facet [4] , ranking facet values [14] and ranking (facet, value) pairs [15] .  ... 
doi:10.1145/3041021.3054195 dblp:conf/www/LiuZHG17 fatcat:uupqiot27jhllj6gp7bz5odv2m

Literature Retrieval for Precision Medicine with Neural Matching and Faceted Summarization

Jiho Noh, Ramakanth Kavuluru
2020 Findings of the Association for Computational Linguistics: EMNLP 2020  
The full architecture benefits from the complementary potential of document-query matching and the novel document transformation approach based on summarization along PM facets.  ...  As such, the retrieval problem is often formulated as ad hoc search but with multiple facets (e.g., disease, mutation) that may need to be incorporated.  ...  The expected output for the MeSH facet is the set of codes that capture entities in the disease and gene variation facets.  ... 
doi:10.18653/v1/2020.findings-emnlp.304 pmid:34541588 pmcid:PMC8444997 fatcat:elsv2diavfe7vawrnwoohyagqm
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