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Identifying complaints from product reviews: a case study on Hindi
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In: Singh, Raghvendra Pratap, Haque, Rejwanul orcid:0000-0003-1680-0099 , Hasanuzzaman, Mohammed orcid:0000-0003-1838-0091 and Way, Andy orcid:0000-0001-5736-5930 (2020) Identifying complaints from product reviews: a case study on Hindi. In: 28th Irish Conference on Artificial Intelligence and Cognitive Science, 7-8 Dec 2020, Dublin, Ireland. (2020)
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English WordNet Taxonomic Random Walk Pseudo-Corpora
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In: Conference papers (2020)
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Synthetic, Yet Natural: Properties of WordNet Random Walk Corpora and the impact of rare words on embedding performance
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In: Conference papers (2019)
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The Observable Representation
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In: Entropy ; Volume 21 ; Issue 3 (2019)
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Short Text Feature Extraction via Node Semantic Coupling and Graph Structures
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In: IFIP Advances in Information and Communication Technology ; 10th International Conference on Intelligent Information Processing (IIP) ; https://hal.inria.fr/hal-02197797 ; 10th International Conference on Intelligent Information Processing (IIP), Oct 2018, Nanning, China. pp.173-182, ⟨10.1007/978-3-030-00828-4_18⟩ (2018)
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Statistical physics of language evolution : the grammaticalization phenomenon ; Physique statistique de l'évolution des langues : le cas de la grammaticalisation
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In: https://tel.archives-ouvertes.fr/tel-01753835 ; Physics [physics]. Université Paris sciences et lettres, 2017. English. ⟨NNT : 2017PSLEE039⟩ (2017)
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PageRank Induced Topology for Real-World Networks
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In: https://hal.archives-ouvertes.fr/hal-01322040 ; 2016 (2016)
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Comparing and Fusing Terrain Network Information
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In: Scalable Uncertainty Management 6th International Conference, SUM 2012, Marburg, Germany, September 17-19, 2012, Proceedings ; Sixth International Conference on Scalable Uncertainty Management (SUM 2012) ; https://hal.archives-ouvertes.fr/hal-00992033 ; Sixth International Conference on Scalable Uncertainty Management (SUM 2012), Sep 2012, Marburg, Germany. pp.459--472, ⟨10.1007/978-3-642-33362-0_35⟩ ; https://link.springer.com/chapter/10.1007%2F978-3-642-33362-0_35 (2012)
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Random Walk on WordNet to Measure Lexical Semantic Relatedness
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In: http://www.d.umn.edu/~tpederse/Pubs/yanbo-report.pdf (2011)
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A Thesaurus-Based Semantic Classification of English Collocations
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In: http://wing.comp.nus.edu.sg/~antho/O/O09/O09-5002.pdf (2009)
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Query expansion using random walk models
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In: http://www.cs.cmu.edu/~callan/Papers/cikm05-kct.pdf (2005)
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Media theory
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In: http://userwww.sfsu.edu/~sergei/MediaTheory.pdf (2002)
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Formalizing Triggers: A Learning Model for Finite Spaces
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In: DTIC AND NTIS (1993)
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A Thesaurus-Based Semantic Classification of English Collocations
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In: http://www.aclclp.org.tw/rocling/2008/OS1_3.pdf
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Measuring the Similarity between TV Programs Using Semantic Relations
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In: http://aclweb.org/anthology/C/C12/C12-1180.pdf
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Extending query translation to cross-language query expansion with markov chain models
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In: http://www.iro.umontreal.ca/~nie/Publication/cao-cikm07.pdf
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Abstract:
Dictionary-based approaches to query translation have been widely used in Cross-Language Information Retrieval (CLIR) experiments. Using these approaches, translation has been not only limited by the coverage of the dictionary, but also affected by translation ambiguities. In this paper we propose a novel method of query translation that combines other types of term relation to complement the dictionary-based translation. This allows extending the literal query translation to related words, which produce a beneficial effect of query expansion in CLIR. In this paper, we model query translation by Markov Chains (MC), where query translation is viewed as a process of expanding query terms to their semantically similar terms in a different language. In MC, terms and their relationships are modeled as a directed graph, and query translation is performed as a random walk in the graph, which propagates probabilities to related terms. This framework allows us incorporating different types of term relation, either between two languages or within the source or the target languages. In addition, the iterative training process of MC allows us to attribute higher probabilities to the target terms more related to the original query, thus offers a solution to the translation ambiguity problem. We evaluated our method on three CLIR benchmark collections, and obtained significant improvements over traditional dictionary-based approaches.
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Keyword:
Algorithm; Cross-Language Information Retrieval; Design; Experimentation Keywords Query Translation; Markov Chain; Query Expansion; Random Walk; Theory
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URL: http://www.iro.umontreal.ca/~nie/Publication/cao-cikm07.pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.409.3393
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2008. Multi-document summarization using cluster-based link analysis
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In: http://www.cs.fiu.edu/%7Elli003/Sum/SIGIR/2008/2.pdf
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Extending query translation to cross-language query expansion with markov chain models
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In: http://www.iro.umontreal.ca/~nie/Publication/Cao-CIKM-07.pdf
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A Novel Bangla Text Corpus Building Method for Efficient Information Retrieval
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In: http://ijcit.org/jcit_papers/vol-1_no-1/JCIT-100708.pdf
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