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Learning Syntactic Rules and Tags with Genetic Algorithms for Information Retrieval and Filtering: An Empirical Basis for Grammatical Rules [article]

Robert M. Losee
1995 arXiv   pre-print
The grammars of natural languages may be learned by using genetic algorithms that reproduce and mutate grammatical rules and part-of-speech tags, improving the quality of later generations of grammatical  ...  Syntactic rules are randomly generated and then evolve; those rules resulting in improved parsing and occasionally improved retrieval and filtering performance are allowed to further propagate.  ...  The data for learning syntactic rules alone runs concurrently for much of this data set with learning syntactic rules and tags together. 6.1 Learning Syntactic Rules and Part-of-Speech Tags Figure 1  ... 
arXiv:cmp-lg/9505005v2 fatcat:h2jmzqggnbb2phckza2czbzwui

Learning syntactic rules and tags with genetic algorithms for information retrieval and filtering: An empirical basis for grammatical rules

Robert M. Losee
1996 Information Processing & Management  
The grammars of natural languages may be learned by using genetic algorithms that reproduce and mutate grammatical rules and part-of-speech tags, improving the quality of later generations of grammatical  ...  Syntactic rules are randomly generated and then evolve; those rules resulting in improved parsing and occasionally improved retrieval and filtering performance are allowed to further propagate.  ...  These syntactic rules and the relationships between grammatical tags and terms may be stored as alleles, individual elements within genes, for analysis with a genetic algorithm.  ... 
doi:10.1016/s0306-4573(96)85005-9 fatcat:wj4dlscfl5gt5lmrhh6vaz3rc4

Learning syntactic rules and tags with genetic algorithms for information retrieval and filtering: An empirical basis for grammatical rules

Losee, Jr.,
1996
The grammars of natural languages may be learned by using genetic algorithms that reproduce and mutate grammatical rules and part-of-speech tags, improving the quality of later generations of grammatical  ...  Syntactic rules are randomly generated and then evolve  ...  The data for learning syntactic rules alone runs concurrently for much of this data set with learning syntactic rules and tags together. 6.1 Learning Syntactic Rules and Part-of-Speech Tags Figure 1  ... 
doi:10.17615/4eny-ax44 fatcat:3rqaohnkkfetljz3uw3wq46pae

Use of a genetic algorithm in brill's transformation-based part-of-speech tagger

Garnett Wilson, Malcolm Heywood
2005 Proceedings of the 2005 conference on Genetic and evolutionary computation - GECCO '05  
This paper describes a variant of Brill's implementation that instead uses a genetic algorithm to generate the instantiated rules and provide an adaptive ranking.  ...  Although not able to make up for the use of a priori knowledge utilized by Brill, the method appears to point the way for an improved solution to the tagging problem.  ...  Valdo Keselj for his questions and providing the Wall Street Journal corpus, as well as the referees for their helpful comments.  ... 
doi:10.1145/1068009.1068352 dblp:conf/gecco/WilsonH05 fatcat:jz6xhhlhbfc7lcrqvlvaeue7l4

Coupled intrinsic and extrinsic human language resource-based query expansion [article]

Bhawani Selvaretnam, Mohammed Belkhatir
2020 arXiv   pre-print
Poor information retrieval performance has often been attributed to the query-document vocabulary mismatch problem which is defined as the difficulty for human users to formulate precise natural language  ...  To alleviate this problem, query expansion processes are applied in order to spawn and integrate additional terms to an initial query.  ...  The mutation and crossover reproduction genetic operators are empirically set at a rate of 10 and 1000 respectively for maximum performance.  ... 
arXiv:2004.11083v1 fatcat:pxro5fus6zhrxiw32a2xbzsiue

A hybrid method for extracting relations between Arabic named entities

Ines Boujelben, Salma Jamoussi, Abdelmajid Ben Hamadou
2014 Journal of King Saud University: Computer and Information Sciences  
The empirical results indicate that the hybrid approach outperformed both the rule-based system (by 12%) and the machine learning-based approaches (by 9%) in terms of the F-score, to achieve 75.2% when  ...  Relation extraction is a very useful task for several natural language processing applications, such as automatic summarization and question answering.  ...  This finding explains Figure 6 Learning curve depending on the number of instances. the fact that morpho-syntactic features are a basis in our learning method.  ... 
doi:10.1016/j.jksuci.2014.06.004 fatcat:avyfhre6mbcq7hzg35yf7jxdei

Named Entity Recognition in Biomedical Domain: A Survey

T. M., D. Manjula, Shruthi Shridhar
2019 International Journal of Computer Applications  
NER has been an active area of research for the past twenty years.  ...  Named Entity Recognition plays an important role in locating and classifying atomic elements into predefined categories such as person names, locations, organizations, expression of times, temporal expressions  ...  It explains the need for Named Entity Recognition in this field along with the various problems in the process including the challenges of extracting information from narrative text and the lack of performance  ... 
doi:10.5120/ijca2019918469 fatcat:n2cumq3lpjgqblf64otnoxal64

E-Mail Authorship Attribution for Computer Forensics [chapter]

Olivier de Vel, Alison Anderson, Mal Corney, George Mohay
2002 Advances in Information Security  
We use an extended set of e-mail document features such as structural characteristics and linguistic patterns together with a Support Vector Machine learning algorithm.  ...  Experiments on a number of e-mail documents generated by different authors on a set of topics gave promising results for both inter-and intra-topic author categorisation.  ...  ., cusum [13] , Thisted and Efron test [32] ), neural networks (e.g., radial basis functions [21] , feedforward neural networks [34] , cascade correlation [37] ), genetic algorithms (e.g., [16] )  ... 
doi:10.1007/978-1-4615-0953-0_9 fatcat:gut64qf5zfgitmousldylfsqsu

The CLSA Model: A Novel Framework for Concept-Level Sentiment Analysis [chapter]

Erik Cambria, Soujanya Poria, Federica Bisio, Rajiv Bajpai, Iti Chaturvedi
2015 Lecture Notes in Computer Science  
Such algorithms are very good at retrieving texts, splitting them into parts, checking the spelling, and counting their words.  ...  But when it comes to interpreting sentences and extracting opinionated information, their capabilities are known to be very limited.  ...  [51] proposed a modified version, which is based on part-of-speech tagging with a shallow syntactic parse indicating grammatical rules.  ... 
doi:10.1007/978-3-319-18117-2_1 fatcat:zlu3xwbijjcbxhq3tngtxqljz4

Mining e-mail content for author identification forensics

O. de Vel, A. Anderson, M. Corney, G. Mohay
2001 SIGMOD record  
An extended set of e-mail document features including structural characteristics and linguistic patterns were derived and, together with a Support Vector Machine learning algorithm, were used for mining  ...  We describe an investigation into e-mail content mining for author identification, or authorship attribution, for the purpose of forensic investigation.  ...  ., cusum [14] , Thisted and Efron test [33] ), neural networks (e.g., radial basis functions [22] , feedforward neural networks [36] , cascade correlation [39] ), genetic algorithms (e.g., [17] )  ... 
doi:10.1145/604264.604272 fatcat:cikcogoeybc4zansdkldeslv2u

Recent progress in automatically extracting information from the pharmacogenomic literature

Yael Garten, Adrien Coulet, Russ B Altman
2010 Pharmacogenomics (London)  
Acknowledgements The authors would like to thank Connie M Oshiro for comments on the manuscript and Nicholas P Tatonetti for useful discussions and assistance creating the figures.  ...  We also thank the three anonymous reviewers for their excellent comments.  ...  ., rule based) and co-occurrence filtering [81] .  ... 
doi:10.2217/pgs.10.136 pmid:21047206 pmcid:PMC3035632 fatcat:7g3jwc4hjfetbb5phmzstzhjeu

Mining the Biomedical Literature in the Genomic Era: An Overview

Hagit Shatkay, Ronen Feldman
2003 Journal of Computational Biology  
most relevant and useful for specific analysis tasks.  ...  This combined abundance of genes and literature produces a major bottleneck for interpreting and planning genome-wide experiments.  ...  ACKNOWLEDGMENTS We thank the ClearForest-Celera team for their work towards the KDD-cup 2002. HS thanks Stephen Edwards, Mark Boguski, and John Wilbur for their collaboration on the GenTheme project.  ... 
doi:10.1089/106652703322756104 pmid:14980013 fatcat:vbwcpl66ujhqdgq4wdjtllbg5e

Index—Volumes 1–89

1997 Artificial Intelligence  
903 Q* algorithm 46 algorithm, use of syntactic and semantic information in the -46 search algorithm 46 Q-Learning algorithm Watkins' -1164 QA question-answering system 46 QA4 language 57  ...  and reasoning with processes 973 exception condition, production rules with an -363 handling 473 exceptionally hard problems 1184 exceptions 67 1 to the rules 1368 excessive crossover rates  ... 
doi:10.1016/s0004-3702(97)80122-1 fatcat:6az7xycuifaerl7kmv7l3x6rpm

MultiLingMine 2016: Modeling, Learning and Mining for Cross/Multilinguality [chapter]

Dino Ienco, Mathieu Roche, Salvatore Romeo, Paolo Rosso, Andrea Tagarelli
2016 Lecture Notes in Computer Science  
This segmenter is based on Rhetorical Structure Theory (RST) for Spanish, and uses lexical and syntactic information to translate rules valid for Spanish into rules for Catalan.  ...  ranking, information extraction, feature engineering, text mining and machine learning.  ...  Zagorka Brodić, professor of French and Serbo-Croatian languages, for the helpful discussions about Latin and Italian languages.  ... 
doi:10.1007/978-3-319-30671-1_83 fatcat:znq74oljzfefrfhzdkpphzekz4

Content-based citation analysis: The next generation of citation analysis

Ying Ding, Guo Zhang, Tamy Chambers, Min Song, Xiaolong Wang, Chengxiang Zhai
2014 Journal of the Association for Information Science and Technology  
Content-based citation analysis (CCA) addresses a citation's value by interpreting each based on their contexts at both syntactic and semantic level.  ...  , more accurate citation prediction, and increased knowledge discovery.  ...  Their results confirmed that the feature set, with the POS tags and added syntactic patterns, was most effective.  ... 
doi:10.1002/asi.23256 fatcat:7gethjhuzva4nejqnd4uthpogi
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