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Machine learned ranking of entity facets
2010
Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '10
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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
2011
Proceedings of the 20th international conference companion on World wide web - WWW '11
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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
2015
Neurocomputing
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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
2010
Information Processing & Management
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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
2018
IJARCCE
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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
2016
Proceedings of the 25th ACM International on Conference on Information and Knowledge Management - CIKM '16
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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]
2018
arXiv
pre-print
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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]
2016
Lecture Notes in Computer Science
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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)
2017
Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval - SIGIR '17
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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]
2013
arXiv
pre-print
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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
2013
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '13
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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]
2015
arXiv
pre-print
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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]
2017
arXiv
pre-print
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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
2017
Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion
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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
2020
Findings of the Association for Computational Linguistics: EMNLP 2020
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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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