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Labeling of Query Words using Conditional Random Field [article]

Satanu Ghosh, Souvick Ghosh, Dipankar Das
<span title="2016-07-29">2016</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
A CRF based machine learning framework was used for labeling the individual words with their corresponding language labels. We used a dictionary based approach for language identification.  ...  This paper describes our approach on Query Word Labeling as an attempt in the shared task on Mixed Script Information Retrieval at Forum for Information Retrieval Evaluation (FIRE) 2015.  ...  NE1: If name entity matches List1, then NE1 = 1, else 0 NE2: If name entity matches List2, then NE2 = 1, else 0 RESULTS In this work, Conditional Random Field (CRF) [13] has been used to build the  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1607.08883v1">arXiv:1607.08883v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ys3g7sh4mvdczaxm5z5le3qzl4">fatcat:ys3g7sh4mvdczaxm5z5le3qzl4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200828185727/https://arxiv.org/ftp/arxiv/papers/1607/1607.08883.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/5b/27/5b27c6e38a28898542787b0cf48a91b4fbe9b367.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1607.08883v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Extracting structured information from user queries with semi-supervised conditional random fields

Xiao Li, Ye-Yi Wang, Alex Acero
<span title="">2009</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ibcfmixrofb3piydwg5wvir3t4" style="color: black;">Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval - SIGIR &#39;09</a> </i> &nbsp;
In this work, we focus on a semi-supervised learning method for CRFs that utilizes two data sources: (1) a small amount of manually-labeled queries, and (2) a large amount of queries in which some word  ...  Our problem could be approached by learning a conditional random field (CRF) model (or other statistical models) in a supervised fashion, but this would require substantial human-annotation effort.  ...  CONDITIONAL RANDOM FIELDS Linear-chain CRFs have been widely used in sequential labeling tasks such as part-of-speech tagging and information extraction [10, 13] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1571941.1572039">doi:10.1145/1571941.1572039</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/sigir/LiWA09.html">dblp:conf/sigir/LiWA09</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gs4z6yay2neohdz6grm5s4csjm">fatcat:gs4z6yay2neohdz6grm5s4csjm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170922080202/https://www.cc.gatech.edu/~zha/CSE8801/query-annotation/p572-li.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3a/d6/3ad67ceff6f1efbc4a83ae9e30cc5d4a2ea908ef.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1571941.1572039"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

Labeling Sequential Data Based on Word Representations and Conditional Random Fields

Xiuying Wang, Bo Xu, Changliang Li, Wendong Ge
<span title="">2015</span> <i title="EJournal Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2uckwik5xjerdg36acn26gjq6e" style="color: black;">International Journal of Machine Learning and Computing</a> </i> &nbsp;
use these preprocessed features as input features of training data to train conditional random fields model.  ...  In this paper, we propose a new method based on word representations and conditional random fields to solve these problems.  ...  Task of Hotel Reservation Query Tagging In the label query task, each query is sequence of word tokens. Our goal is to assign a label from a set of predefined fields to each word token.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18178/ijmlc.2015.5.6.548">doi:10.18178/ijmlc.2015.5.6.548</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vk7vwiuulfcw7hhxttmju7llua">fatcat:vk7vwiuulfcw7hhxttmju7llua</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190428195140/http://www.ijmlc.org/vol5/548-C3001.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ea/5e/ea5e6056c6853d89e336c1008a2dbd2d6500ec7b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18178/ijmlc.2015.5.6.548"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Finding the Topic of a Set of Images [article]

Gonzalo Vaca-Castano
<span title="2016-06-25">2016</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We also present a new Conditional Random Field (CRF) word mapping algorithm that preserves the semantic similarity of the mapped words, increasing the performance of the results over the baseline.  ...  The words or tags associated to each query are processed jointly in a word selection algorithm using random walks that allows to refine the search topic, rejecting words that are not part of the topic  ...  by means of a Conditional Random Field that exploit distances in the word embedding space to define the pairwise edge potentials.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1606.07921v1">arXiv:1606.07921v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/e6jpx6mhevgp7mqfekwem7jvmu">fatcat:e6jpx6mhevgp7mqfekwem7jvmu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20191024143352/https://arxiv.org/pdf/1606.07921v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/4d/ba/4dba7e19e2958d8ab75261219747aebc675c6f8a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1606.07921v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Context-Aware Online Commercial Intention Detection [chapter]

Derek Hao Hu, Dou Shen, Jian-Tao Sun, Qiang Yang, Zheng Chen
<span title="">2009</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
In this paper, we present a new algorithm framework based on skip-chain conditional random field (SCCRF) for automatically classifying Web queries according to context-based online commercial intention  ...  Just like the common Web search queries, the queries with commercial intention are usually very short.  ...  Acknowledgement Qiang Yang and Derek Hao Hu thank the support of Microsoft Research Project MRA07/08.EG01.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-05224-8_12">doi:10.1007/978-3-642-05224-8_12</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5kn7yth5hnguzdzt2uymlqtu4i">fatcat:5kn7yth5hnguzdzt2uymlqtu4i</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170808210128/http://home.cse.ust.hk/~qyang/Docs/2009/acml2009.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/cf/09/cf09d1b55dc690061bcaf886ca3b8f7ea088976a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-05224-8_12"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Signature-Based Retrieval of Scanned Documents Using Conditional Random Fields [chapter]

Harish Srinivasan, Sargur Srihari
<span title="">2009</span> <i title="Springer Berlin Heidelberg"> Computational Methods for Counterterrorism </i> &nbsp;
Indexing is done using (i) a model based on Conditional Random Fields (CRF) to label extracted segments of scanned documents as Machine-Print, Signature and Noise, (ii) a technique using support vector  ...  In searching a large repository of scanned documents, a task of interest is that of retrieving documents from a database using a signature image as a query.  ...  Conditional Random Field model description A model based on Conditional Random Fields is used to label each of the patches identified using the labels of the neighboring patches.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-01141-2_2">doi:10.1007/978-3-642-01141-2_2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/r72zxfj6jzgzzpolt5ctt44ka4">fatcat:r72zxfj6jzgzzpolt5ctt44ka4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200710075421/https://www.springer.com/cda/content/document/cda_downloaddocument/9783642011405-c1.pdf?SGWID=0-0-45-754106-p173898208" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b7/5a/b75a59e6b57b8b8c9f321bdfdd3c653fbfbaae6f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-01141-2_2"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Recurrent conditional random field for language understanding

Kaisheng Yao, Baolin Peng, Geoffrey Zweig, Dong Yu, Xiaolong Li, Feng Gao
<span title="">2014</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rc5jnc4ldvhs3dswicq5wk3vsq" style="color: black;">2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</a> </i> &nbsp;
In the word-labeling task, the RNN is used analogously to the more traditional conditional random field (CRF) to assign a label to each word in an input sequence, and has been shown to significantly outperform  ...  We term the resulting model a "recurrent conditional random field" and demonstrate its effectiveness on the ATIS travel domain dataset and a variety of web-search language understanding datasets.  ...  Perhaps the most obvious approach to this task is the use of Conditional Random Fields (CRFs) [23] , in which an exponential model is used to compute the probability of a label sequence given the input  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icassp.2014.6854368">doi:10.1109/icassp.2014.6854368</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icassp/YaoPZYLG14.html">dblp:conf/icassp/YaoPZYLG14</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/st27klxoezcibccjnyuj26mezm">fatcat:st27klxoezcibccjnyuj26mezm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20160104160108/http://research.microsoft.com/pubs/216994/rcrf_v9.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a0/be/a0be425d538224a795ab2ff36aed5827beb68db7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icassp.2014.6854368"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Improving verbose queries using subset distribution

Xiaobing Xue, Samuel Huston, W. Bruce Croft
<span title="">2010</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6g37zvjwwrhv3dizi6ffue642m" style="color: black;">Proceedings of the 19th ACM international conference on Information and knowledge management - CIKM &#39;10</a> </i> &nbsp;
A novel Conditional Random Field model is proposed to generate the distribution of sub-queries.  ...  Specifically, sub-query selection is considered as a sequential labeling problem, where each query word in a verbose query is assigned a label of "keep" or "don't keep".  ...  Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect those of the sponsor.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1871437.1871572">doi:10.1145/1871437.1871572</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cikm/XueHC10.html">dblp:conf/cikm/XueHC10</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/j343rsvvandola2uzi4bxztafu">fatcat:j343rsvvandola2uzi4bxztafu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180721182410/http://ciir-publications.cs.umass.edu/pub/web/getpdf.php?id=950" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f6/09/f6093f9e76e4355d20615b85f64295f873381e65.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1871437.1871572"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

Extractive Text Summarization for Social News using Hybrid Techniques in Opinion Mining

<span title="2020-02-29">2020</span> <i title="Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/h673cvfolnhl3mnbjxkhtxdtg4" style="color: black;">International Journal of Engineering and Advanced Technology</a> </i> &nbsp;
The existing work recommends a technique of hybrid text summarization that's a blend of CRF (conditional random fields) and LSA (Latent Semantic Analysis) which being highly adhesive with low redundant  ...  The technique of LSA extracts hidden semantic structures within words/sentences that being commonly utilized in the process of summarization.  ...  Conditional Random Fields CRFs (Conditional Random Fields)can be considered as a discriminative undirected probabilistic graphical model which is adopted for parsing/labeling the sequential data.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.35940/ijeat.b3356.029320">doi:10.35940/ijeat.b3356.029320</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7vwnlgsef5arpllozo24oraotu">fatcat:7vwnlgsef5arpllozo24oraotu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200307024402/https://www.ijeat.org/wp-content/uploads/papers/v9i3/B3356129219.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.35940/ijeat.b3356.029320"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Sparse hidden-dynamics conditional random fields for user intent understanding

Yelong Shen, Jun Yan, Shuicheng Yan, Lei Ji, Ning Liu, Zheng Chen
<span title="">2011</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/s4hirppq3jalbopssw22crbwwa" style="color: black;">Proceedings of the 20th international conference on World wide web - WWW &#39;11</a> </i> &nbsp;
those classical solutions such as Support Vector Machine (SVM), Conditional Random Field (CRF) and Latnet-Dynamic Conditional Random Field (LDCRF).  ...  In this paper, we propose a novel Sparse Hidden-Dynamic Conditional Random Fields (SHDCRF) model for user intent learning from their search sessions.  ...  [45] , and class label dependence, such as using Conditional Random Fields (CRFs) and Hidden Markov Model (HMM) [5, 20, 36] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1963405.1963411">doi:10.1145/1963405.1963411</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/www/ShenYYJLC11.html">dblp:conf/www/ShenYYJLC11</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/uhxpxl72ifh4hfllhmpy6ecdpu">fatcat:uhxpxl72ifh4hfllhmpy6ecdpu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170809024935/http://www.ra.ethz.ch/cdstore/www2011/proceedings/p7.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/bf/85/bf85403053e5e2c23276493234c6b7bff45af30a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1963405.1963411"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

Unsupervised query segmentation using click data

Julia Kiseleva, Qi Guo, Eugene Agichtein, Daniel Billsus, Wei Chai
<span title="">2010</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/s4hirppq3jalbopssw22crbwwa" style="color: black;">Proceedings of the 19th international conference on World wide web - WWW &#39;10</a> </i> &nbsp;
The resulting queries can be used to more accurately search product databases, and potentially improve result presentation and query suggestion.  ...  We describe preliminary results of experiments with an unsupervised framework for query segmentation, transforming keyword queries into structured queries.  ...  In Proc. of KDD 2004. [3] X. Yu and H. Shi. Query Segmentation Using Conditional Random Fields. In Proc. of KEYS 2009.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1772690.1772839">doi:10.1145/1772690.1772839</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/www/KiselevaGABC10.html">dblp:conf/www/KiselevaGABC10</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/haum5dmpobbjveferik6ccff5a">fatcat:haum5dmpobbjveferik6ccff5a</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170811144957/http://www.ra.ethz.ch/cdstore/www2010/www/p1131.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/48/71/4871ae15340af972a4951462bd3680929a607c4c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1772690.1772839"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

Extracting temporal constraints from clinical research eligibility criteria using conditional random fields

Zhihui Luo, Stephen B Johnson, Albert M Lai, Chunhua Weng
<span title="2011-10-22">2011</span> <i title="American Medical Informatics Association"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/g6q27b56yzeupjryv6lby2r2pa" style="color: black;">AMIA Annual Symposium Proceedings</a> </i> &nbsp;
We manually annotated 150 free-text eligibility criteria using the temporal labels and trained a parser using Conditional Random Fields (CRFs) to automatically extract temporal expressions from eligibility  ...  We illustrate the application of temporal extraction with the use cases of question answering and free-text criteria querying.  ...  Its contents are solely the responsibility of the authors and do not necessarily represent the official view of NIH.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/22195142">pmid:22195142</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC3243135/">pmcid:PMC3243135</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2i47bqpih5hkpgtelijqa35o3q">fatcat:2i47bqpih5hkpgtelijqa35o3q</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200209232503/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC3243135&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3e/fd/3efdc081d10139cfb3b4be71821106052e7f3515.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3243135" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

CRF-based active learning for Chinese named entity recognition

Lin Yao, Chengjie Sun, Shaofeng Li, Xiaolong Wang, Xuan Wang
<span title="">2009</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hyrfp4q26bahtlwucwlaapnfwy" style="color: black;">2009 IEEE International Conference on Systems, Man and Cybernetics</a> </i> &nbsp;
Conditional Random Fields (CRFs) have been used for many sequence labeling tasks and got excellent results. Further, the supervised model strongly depends on the huge training data.  ...  On Sighan bakeoff 2006 MSRA NER corpus, an F1 score of 77.2% is achieved by using only 10,000 labeled training sentences chosen by the proposed active learning strategy.  ...  CONDITIONAL RANDOM FIELD Similar to the Hidden Markov Models (HMMs) [12] , Conditional Random Fields (CRFs) [13] are a probabilistic framework for labeling and segmenting sequential data.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icsmc.2009.5346315">doi:10.1109/icsmc.2009.5346315</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/smc/YaoSLWW09.html">dblp:conf/smc/YaoSLWW09</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vrsj4bvn7bdkdblsuk5z4ujkma">fatcat:vrsj4bvn7bdkdblsuk5z4ujkma</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170809023055/http://vigir.missouri.edu/~gdesouza/Research/Conference_CDs/IEEE_SMC_2009/PDFs/734.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/27/12/27129da9b36e3769fcc7265c4e58a0ba6d33fdac.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icsmc.2009.5346315"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

A discrete direct retrieval model for image and video retrieval

Shaolei Feng, R. Manmatha
<span title="">2008</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2xkv6wxeijegdpwsmlltwaoyje" style="color: black;">Proceedings of the 2008 international conference on Content-based image and video retrieval - CIVR &#39;08</a> </i> &nbsp;
This paper proposes a formal framework for image and video retrieval using discrete Markov random fields (MRF). The training dataset consists of images with keywords (regions are not labeled).  ...  The model directly ranks all test images according to the posterior probability of an image given a query.  ...  MARKOV RANDOM FIELD FOR IMAGE RETRIEVAL Markov random fields (MRFs) have been widely used to model the joint distribution of a set of random variables.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1386352.1386407">doi:10.1145/1386352.1386407</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/civr/FengM08.html">dblp:conf/civr/FengM08</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bptc2u4ml5fujnmh4prlca4otm">fatcat:bptc2u4ml5fujnmh4prlca4otm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170706133559/https://works.bepress.com/r_manmatha/38/download/" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a9/a1/a9a18414a5c1925b9844d14c7929057a03149eb9.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1386352.1386407"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

Segmenting and Labeling Query Sequences in a Multidatabase Environment [chapter]

Aybar C. Acar, Amihai Motro
<span title="">2011</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
We propose a method in which a discriminative probabilistic model (a Conditional Random Field) is trained with pre-labeled sequences.  ...  15% of queries in the sequence are spurious).  ...  Conditional Random Fields A common approach to segmenting sequence data and labeling the constituent parts has been the use of probabilistic graphical models.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-25109-2_24">doi:10.1007/978-3-642-25109-2_24</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dgnc766r2re5pkotwxwiqpty7y">fatcat:dgnc766r2re5pkotwxwiqpty7y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170808194018/http://cs.gmu.edu/~ami/research/publications/pdf/coopis11.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/5e/93/5e937d6fd734e22cb4f35adeb680f8c2052e91f5.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-25109-2_24"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>
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