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New Information Content Glossary Relatedness (ICGR) Approach for Short Text Similarity (STS) Tasks

Ali Muftah BenOmran, Mohd Juzaiddin Ab Aziz
2019 Journal of Computer Science  
Knowledge-based methods using a gloss overlap have a similar limitation to the corpus-based methods, where they lead to the loss of many valuable relatedness features that determine a more accurate measurement  ...  Other corpusbased methods use a cut-off threshold that is determined experimentally to reduce the semantic space and to increase the search for a more accurate semantic space.  ...  The final step was the ICGR-similarity overlap as a measure of the semantic similarities between short texts. The dataset by Li et al. (2006) was used in these experiments.  ... 
doi:10.3844/jcssp.2019.769.784 fatcat:gb4dpijj3jca7ldmwzbv5752pm

An Empirical Study of Word Sense Disambiguation

Srinivas M., B.Padmaja Rani
2016 International Journal on Natural Language Computing  
We have presented a brief history of WSD, discussed the Supervised, Unsupervised, and Knowledge-based approaches for WSD.  ...  Word Sense Disambiguation (WSD) is an important area which has an impact on improving the performance of applications of computational linguistics such as machine translation, information retrieval, text  ...  These approaches identify word senses from input text by dividing word occurrences. New occurrences are clustered based on the induced clusters.  ... 
doi:10.5121/ijnlc.2016.5503 fatcat:tcp7oi4owbfmpc52nvrsceo3di

A Review on WordNet and Vector Space Analysis for Short-text Semantic Similarity

2017 International Journal of Innovations in Engineering and Technology  
In vector space model words can be represented as numeric vectors based on different semantic similarity measures, the similarity between the word numeric vectors can be calculated with the semantic measures  ...  It is a online lexical database designed for use under the program control, it uses the measure like for calculating the semantic similarity between the concepts.  ...  A new word vector is proposed for each sentence using information from lexical database that calculate the weights of the semantic similarity between the texts by obtaining similarity from the corpus-based  ... 
doi:10.21172/ijiet.81.018 fatcat:7fdugo52c5gonp4e7nmho6kdcq

Toward Semantic XML Clustering [chapter]

Andrea Tagarelli, Sergio Greco
2006 Proceedings of the 2006 SIAM International Conference on Data Mining  
We propose a framework for clustering semantically cohesive XML structures based on a transactional representation model.  ...  In this context, we address the problem of clustering XML data according to structure as well as content features enriched with lexical ontology knowledge.  ...  This idea has been formalized in a measure of semantic relatedness between word senses based on the notion of extended gloss overlap [4] , which has the merit of considering phrasal matches and weighting  ... 
doi:10.1137/1.9781611972764.17 dblp:conf/sdm/TagarelliG06 fatcat:c5o2ql5rnncrhnfqaoyhnssome

Word Sense Disambiguation for XML Structure Feature Generation [chapter]

Andrea Tagarelli, Mario Longo, Sergio Greco
2009 Lecture Notes in Computer Science  
Experiments with data from various application domains are discussed, showing that our approach can be effectively used to generate structural semantic features.  ...  For this purpose, we define an unsupervised word sense disambiguation method to select the most appropriate meaning for each element contextually to its respective XML path.  ...  of finding (semantically useful) overlaps between glosses.  ... 
doi:10.1007/978-3-642-02121-3_14 fatcat:nf6oiuudvvfc7pdhupfpz5ajey

Word sense disambiguation using hybrid swarm intelligence approach

Wafaa AL-Saiagh, Sabrina Tiun, Ahmed AL-Saffar, Suryanti Awang, A. S. Al-khaleefa, Francesco Pappalardo
2018 PLoS ONE  
Different semantic measures have been utilized in this model as objective functions for the proposed hybrid PSO.  ...  The literature shows a vast number of techniques used for the process of WSD.  ...  Acknowledgments The authors would like to express their deep gratitude to Universiti Kebangsaan Malaysia (UKM) for providing financial support by Dana Impak Perdana research grant no. DIP-2016-033.  ... 
doi:10.1371/journal.pone.0208695 pmid:30571777 pmcid:PMC6301655 fatcat:4hpvmkjpmfeapa2wjsvej4if5e

Clustering of semantically enriched short texts

Marek Kozlowski, Henryk Rybinski
2018 Journal of Intelligent Information Systems  
In addition, we test the possibilities of improving the quality of clustering ultra-short texts by means of enriching them semantically.  ...  The paper is devoted to the issue of clustering small sets of very short texts.  ...  Acknowledgments We would like to thank three anonymous referees for their valuable and constructive comments, which helped us to improve the quality of this article.  ... 
doi:10.1007/s10844-018-0541-4 fatcat:eipabygtdrdr3ji7wqth6vic4a

Neural Network Based Document Clustering Using WordNet Ontologies

Chihli Hung, Stefan Wermter
2005 International Journal of Hybrid Intelligent Systems  
Three novel text vector representation approaches for neural network based document clustering are proposed.  ...  This hypernym semantic relationship supplements the neural model in document clustering.  ...  10,000 full-text news data set.  ... 
doi:10.3233/his-2004-13-402 fatcat:42vnhgv67bcknjhim5o5td42q4

UoW: NLP techniques developed at the University of Wolverhampton for Semantic Similarity and Textual Entailment

Rohit Gupta, Hanna Bechara, Ismail El Maarouf, Constantin Orasan
2014 Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)  
Our system performed satisfactorily and obtained 0.711 Pearson correlation for the semantic relatedness task and 78.52% accuracy for the textual entailment task.  ...  We proposed a machine learning approach which is based on features extracted using Typed Dependencies, Paraphrasing, Machine Translation evaluation metrics, Quality Estimation metrics and Corpus Pattern  ...  ., 2006) exploited WordNet in various ways to extract the semantic relatedness. Banerjee and Pedersen (2003) presented a measure using extended gloss overlap.  ... 
doi:10.3115/v1/s14-2139 dblp:conf/semeval/GuptaBMO14 fatcat:7eihg6a5ufcjxmln3nsjdxigoa

Evolution of Semantic Similarity – A Survey [article]

Dhivya Chandrasekaran, Vijay Mago
2021 arXiv   pre-print
The versatility of natural language makes it difficult to define rule-based methods for determining semantic similarity measures.  ...  Estimating the semantic similarity between text data is one of the challenging and open research problems in the field of Natural Language Processing (NLP).  ...  ACKNOWLEDGMENTS The authors would like to extend our gratitude to the research team in the DaTALab at Lakehead University for their support, in particular Abhijit Rao, Mohiuddin Qudar, Punardeep Sikka  ... 
arXiv:2004.13820v2 fatcat:fh7jkq7cyvczdnxarhscya2u4u

An Intelligent Hybrid Approach for Improving Recall in Electronic Discovery

Eniafe F. Ayetiran
2013 International Conference on Legal Knowledge and Information Systems  
of direct text matching.  ...  This approach takes ideas from Natural Language Processing (Word sense disambiguation) and Information Retrieval in enhancing retrieval of responsive documents using the semantics of query terms instead  ...  This approach is named gloss overlap or the Lesk algorithm after its author [6] . It is one of the first algorithms developed for the semantic disambiguation of all words in unrestricted text.  ... 
dblp:conf/jurix/Ayetiran13 fatcat:hysqsmxpgzhwtdgxlghaq4gav4

A Large-Scale Multilingual Disambiguation of Glosses [article]

José Camacho Collados and Claudio Delli Bovi and Alessandro Raganato and Roberto Navigli
2016 arXiv   pre-print
information of equivalent definitions across different languages to provide context for disambiguation, and then we combine it with a semantic similarity-based refinement.  ...  Our approach for the construction and disambiguation of the corpus builds upon the structure of a large multilingual semantic network and a state-of-the-art disambiguation system; first, we gather complementary  ...  We follow the original setting of (Camacho-Collados et al., 2015a) and only cluster a pair of Wikipedia articles if their similarity, calculated by using the square-rooted Weighted Overlap comparison  ... 
arXiv:1608.06718v1 fatcat:m2va7zpvebhcbau75cza4o23gy

A semantic approach for text clustering using WordNet and lexical chains

Tingting Wei, Yonghe Lu, Huiyou Chang, Qiang Zhou, Xianyu Bao
2015 Expert systems with applications  
To overcome this problem, introducing semantic information from ontology such as WordNet has been widely used to improve the quality of text clustering.  ...  However, there still exist several challenges, such as synonym and polysemy, high dimensionality, extracting core semantics from texts, and assigning appropriate description for the generated clusters.  ...  Acknowledgements This research is supported by National Key Technology R&D Program for the 12th five-year plan (Grant No. 2012BAK17B08), National Natural Science Foundation of China (Grant No. 71373291  ... 
doi:10.1016/j.eswa.2014.10.023 fatcat:xip4rlc3dnbyxcgtfwbajy5zwa

Semantic Analysis and Thematic Annotation [chapter]

Federico Boschetti, Monica Berti
2019 Digital Classical Philology  
The second part of the contribution, devoted to the syntagmatic axis, is focused on the semantic and thematic annotation of classical and biblical texts.  ...  The automated procedures to create the basis for a new Ancient Greek WordNet from bilingual dictionaries (mainly: the LSJ) will be illustrated and the on-going project named Homeric Greek WordNet, validated  ...  Topic modeling is based on automated procedures for the identification of word/document clusters.  ... 
doi:10.1515/9783110599572-018 fatcat:kyokyzxvajemjivzj5lf3fbhsq

Constrained Semi-supervised Learning in the Presence of Unanticipated Classes

Bhavana Bharat Dalvi
2016 SIGIR Forum  
In our method, based on overlap of coordinate term cluster with the Hyponym Concept dataset, we extend the labels to whole cluster.  ...  In our method, based on overlap of coordinate term cluster with the Hyponym Concept dataset, we extend the labels to the whole cluster.  ...  However many columns have information that is useful only within a site (e.g., navigational links) and many are overlapping. To solve this problem we use the redundancy of information on the Web.  ... 
doi:10.1145/2888422.2888447 fatcat:nqtcg5n5brbvphvh4c3clyrcei
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