Redalyc.Sentence Similarity Computation Based on Wordnet
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Evaluation of Stop Word Lists in Chinese Language
Evaluation of Stop Word Lists in Chinese Language Feng Zou, Fu Lee Wang, Xiaotie Deng, Song Han Department of Computer Science, City University of Hong Kong Kowloon Tong, Hong Kong [email protected] {flwang, csdeng, shan00}@cityu.edu.hk Abstract In modern information retrieval systems, effective indexing can be achieved by removal of stop words. Till now many stop word lists have been developed for English language. However, no standard stop word list has been constructed for Chinese language yet. With the fast development of information retrieval in Chinese language, exploring the evaluation of Chinese stop word lists becomes critical. In this paper, to save the time and release the burden of manual comparison, we propose a novel stop word list evaluation method with a mutual information-based Chinese segmentation methodology. Experiments have been conducted on training texts taken from a recent international Chinese segmentation competition. Results show that effective stop word lists can improve the accuracy of Chinese segmentation significantly. In order to produce a stop word list which is widely 1. Introduction accepted as a standard, it is extremely important to In information retrieval, a document is traditionally compare the performance of different stop word list. On indexed by frequency of words in the documents (Ricardo the other hand, it is also essential to investigate how a stop & Berthier, 1999; Rijsbergen, 1975; Salton & Buckley, word list can affect the completion of related tasks in 1988). Statistical analysis through documents showed that language processing. With the fast growth of online some words have quite low frequency, while some others Chinese documents, the evaluation of these stop word lists act just the opposite (Zipf, 1932). -
An Arabic Wordnet with Ontologically Clean Content
Applied Ontology (2021) IOS Press The Arabic Ontology – An Arabic Wordnet with Ontologically Clean Content Mustafa Jarrar Birzeit University, Palestine [email protected] Abstract. We present a formal Arabic wordnet built on the basis of a carefully designed ontology hereby referred to as the Arabic Ontology. The ontology provides a formal representation of the concepts that the Arabic terms convey, and its content was built with ontological analysis in mind, and benchmarked to scientific advances and rigorous knowledge sources as much as this is possible, rather than to only speakers’ beliefs as lexicons typically are. A comprehensive evaluation was conducted thereby demonstrating that the current version of the top-levels of the ontology can top the majority of the Arabic meanings. The ontology consists currently of about 1,300 well-investigated concepts in addition to 11,000 concepts that are partially validated. The ontology is accessible and searchable through a lexicographic search engine (http://ontology.birzeit.edu) that also includes about 150 Arabic-multilingual lexicons, and which are being mapped and enriched using the ontology. The ontology is fully mapped with Princeton WordNet, Wikidata, and other resources. Keywords. Linguistic Ontology, WordNet, Arabic Wordnet, Lexicon, Lexical Semantics, Arabic Natural Language Processing Accepted by: 1. Introduction The importance of linguistic ontologies and wordnets is increasing in many application areas, such as multilingual big data (Oana et al., 2012; Ceravolo, 2018), information retrieval (Abderrahim et al., 2013), question-answering and NLP-based applications (Shinde et al., 2012), data integration (Castanier et al., 2012; Jarrar et al., 2011), multilingual web (McCrae et al., 2011; Jarrar, 2006), among others. -
PSWG: an Automatic Stop-Word List Generator for Persian Information
Vol. 2(5), Apr. 2016, pp. 326-334 PSWG: An Automatic Stop-word List Generator for Persian Information Retrieval Systems Based on Similarity Function & POS Information Mohammad-Ali Yaghoub-Zadeh-Fard1, Behrouz Minaei-Bidgoli1, Saeed Rahmani and Saeed Shahrivari 1Iran University of Science and Technology, Tehran, Iran 2Freelancer, Tehran, Iran *Corresponding Author's E-mail: [email protected] Abstract y the advent of new information resources, search engines have encountered a new challenge since they have been obliged to store a large amount of text materials. This is even more B drastic for small-sized companies which are suffering from a lack of hardware resources and limited budgets. In such a circumstance, reducing index size is of paramount importance as it is to maintain the accuracy of retrieval. One of the primary ways to reduce the index size in text processing systems is to remove stop-words, frequently occurring terms which do not contribute to the information content of documents. Even though there are manually built stop-word lists almost for all languages in the world, stop-word lists are domain-specific; in other words, a term which is a stop- word in a specific domain may play an indispensable role in another one. This paper proposes an aggregated method for automatically building stop-word lists for Persian information retrieval systems. Using part of speech tagging and analyzing statistical features of terms, the proposed method tries to enhance the accuracy of retrieval and minimize potential side effects of removing informative terms. The experiment results show that the proposed approach enhances the average precision, decreases the index storage size, and improves the overall response time. -
Verbnet Based Citation Sentiment Class Assignment Using Machine Learning
(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 11, No. 9, 2020 VerbNet based Citation Sentiment Class Assignment using Machine Learning Zainab Amjad1, Imran Ihsan2 Department of Creative Technologies Air University, Islamabad, Pakistan Abstract—Citations are used to establish a link between time-consuming and complicated. To resolve this issue there articles. This intent has changed over the years, and citations are exists many researchers [7]–[9] who deal with the sentiment now being used as a criterion for evaluating the research work or analysis of citation sentences to improve bibliometric the author and has become one of the most important criteria for measures. Such applications can help scholars in the period of granting rewards or incentives. As a result, many unethical research to identify the problems with the present approaches, activities related to the use of citations have emerged. That is why unaddressed issues, and the present research gaps [10]. content-based citation sentiment analysis techniques are developed on the hypothesis that all citations are not equal. There are two existing approaches for Citation Sentiment There are several pieces of research to find the sentiment of a Analysis: Qualitative and Quantitative [7]. Quantitative citation, however, only a handful of techniques that have used approaches consider that all citations are equally important citation sentences for this purpose. In this research, we have while qualitative approaches believe that all citations are not proposed a verb-oriented citation sentiment classification for equally important [9]. The quantitative approach uses citation researchers by semantically analyzing verbs within a citation text count to rank a research paper [8] while the qualitative using VerbNet Ontology, natural language processing & four approach analyzes the nature of citation [10]. -
Towards a Cross-Linguistic Verbnet-Style Lexicon for Brazilian Portuguese
Towards a cross-linguistic VerbNet-style lexicon for Brazilian Portuguese Carolina Scarton, Sandra Alu´ısio Center of Computational Linguistics (NILC), University of Sao˜ Paulo Av. Trabalhador Sao-Carlense,˜ 400. 13560-970 Sao˜ Carlos/SP, Brazil [email protected], [email protected] Abstract This paper presents preliminary results of the Brazilian Portuguese Verbnet (VerbNet.Br). This resource is being built by using other existing Computational Lexical Resources via a semi-automatic method. We identified, automatically, 5688 verbs as candidate members of VerbNet.Br, which are distributed in 257 classes inherited from VerbNet. These preliminary results give us some directions of future work and, since the results were automatically generated, a manual revision of the complete resource is highly desirable. 1. Introduction the verb to load. To fulfill this gap, VerbNet has mappings The task of building Computational Lexical Resources to WordNet, which has deeper semantic relations. (CLRs) and making them publicly available is one of Brazilian Portuguese language lacks CLRs. There are some the most important tasks of Natural Language Processing initiatives like WordNet.Br (Dias da Silva et al., 2008), that (NLP) area. CLRs are used in many other applications is based on and aligned to WordNet. This resource is the in NLP, such as automatic summarization, machine trans- most complete for Brazilian Portuguese language. How- lation and opinion mining. Specially, CLRs that treat the ever, only the verb database is in an advanced stage (it syntactic and semantic behaviour of verbs are very impor- is finished, but without manual validation), currently con- tant to the tasks of information retrieval (Croch and King, sisting of 5,860 verbs in 3,713 synsets. -
Natural Language Processing Security- and Defense-Related Lessons Learned
July 2021 Perspective EXPERT INSIGHTS ON A TIMELY POLICY ISSUE PETER SCHIRMER, AMBER JAYCOCKS, SEAN MANN, WILLIAM MARCELLINO, LUKE J. MATTHEWS, JOHN DAVID PARSONS, DAVID SCHULKER Natural Language Processing Security- and Defense-Related Lessons Learned his Perspective offers a collection of lessons learned from RAND Corporation projects that employed natural language processing (NLP) tools and methods. It is written as a reference document for the practitioner Tand is not intended to be a primer on concepts, algorithms, or applications, nor does it purport to be a systematic inventory of all lessons relevant to NLP or data analytics. It is based on a convenience sample of NLP practitioners who spend or spent a majority of their time at RAND working on projects related to national defense, national intelligence, international security, or homeland security; thus, the lessons learned are drawn largely from projects in these areas. Although few of the lessons are applicable exclusively to the U.S. Department of Defense (DoD) and its NLP tasks, many may prove particularly salient for DoD, because its terminology is very domain-specific and full of jargon, much of its data are classified or sensitive, its computing environment is more restricted, and its information systems are gen- erally not designed to support large-scale analysis. This Perspective addresses each C O R P O R A T I O N of these issues and many more. The presentation prioritizes • identifying studies conducting health service readability over literary grace. research and primary care research that were sup- We use NLP as an umbrella term for the range of tools ported by federal agencies. -
Ontology Based Natural Language Interface for Relational Databases
Available online at www.sciencedirect.com ScienceDirect Procedia Computer Science 92 ( 2016 ) 487 – 492 2nd International Conference on Intelligent Computing, Communication & Convergence (ICCC-2016) Srikanta Patnaik, Editor in Chief Conference Organized by Interscience Institute of Management and Technology Bhubaneswar, Odisha, India Ontology Based Natural Language Interface for Relational Databases a b B.Sujatha* , Dr.S.Viswanadha Raju a. Assistant Professor, Department of CSE, Osmania University, Hyderabad, India b. Professor, Dept. Of CSE, JNTU college of Engineering, Jagityal, Karimnagar, India Abstract Developing Natural Language Query Interface to Relational Databases has gained much interest in research community since forty years. This can be termed as structured free query interface as it allows the users to retrieve the data from the database without knowing the underlying schema. Structured free query interface should address majorly two problems. Querying the system with Natural Language Interfaces (NLIs) is comfortable for the naive users but it is difficult for the machine to understand. The other problem is that the users can query the system with different expressions to retrieve the same information. The different words used in the query can have same meaning and also the same word can have multiple meanings. Hence it is the responsibility of the NLI to understand the exact meaning of the word in the particular context. In this paper, a generic NLI Database system has proposed which contains various phases. The exact meaning of the word used in the query in particular context is obtained using ontology constructed for customer database. The proposed system is evaluated using customer database with precision, recall and f1-measure. -
INFORMATION RETRIEVAL SYSTEM for SILT'e LANGUAGE Using
INFORMATION RETRIEVAL SYSTEM FOR SILT’E LANGUAGE Using BM25 weighting Abdulmalik Johar 1 Lecturer, Department of information system, computing and informatics college, Wolkite University, Ethiopia ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - The main aim of an information retrieval to time in the Silt’e zone. The growth of digital text system is to extract appropriate information from an information makes the utilization and access of the right enormous collection of data based on user’s need. The basic information difficult. Therefore, an information retrieval concept of the information retrieval system is that when a system needed to store, organize and helps to access Silt’e digital text information user sends out a query, the system would try to generate a list of related documents ranked in order, according to their 1.2. Literature Review degree of relevance. Digital unstructured Silt’e text documents increase from time to time. The growth of digital The Writing System of Silt’e Language text information makes the utilization and access of the right The accurate period that the Ge'ez character set was used information difficult. Thus, developing an information for Silt'e writing system is not known. However, since the retrieval system for Silt’e language allows searching and 1980s, Silt'e has been written in the Ge'ez alphabet, or retrieving relevant documents that satisfy information need Ethiopic script, writing system, originally developed for the of users. In this research, we design probabilistic information now extinct Ge'ez language and most known today in its use retrieval system for Silt’e language. The system has both for Amharic and Tigrigna [9]. -
The Applicability of Natural Language Processing (NLP) To
THE AMERICAN ARCHIVIST The Applicability of Natural Language Processing (NLP) to Archival Properties and Downloaded from http://meridian.allenpress.com/american-archivist/article-pdf/61/2/400/2749134/aarc_61_2_j3p8200745pj34v6.pdf by guest on 01 October 2021 Objectives Jane Greenberg Abstract Natural language processing (NLP) is an extremely powerful operation—one that takes advantage of electronic text and the computer's computational capabilities, which surpass human speed and consistency. How does NLP affect archival operations in the electronic environment? This article introduces archivists to NLP with a presentation of the NLP Continuum and a description of the Archives Axiom, which is supported by an analysis of archival properties and objectives. An overview of the basic information retrieval (IR) framework is provided and NLP's application to the electronic archival environment is discussed. The analysis concludes that while NLP offers advantages for indexing and ac- cessing electronic archives, its incapacity to understand records and recordkeeping systems results in serious limitations for archival operations. Introduction ince the advent of computers, society has been progressing—at first cautiously, but now exponentially—from a dependency on printed text, to functioning almost exclusively with electronic text and other elec- S 1 tronic media in an array of environments. Underlying this transition is the growing accumulation of massive electronic archives, which are prohibitively expensive to index by traditional manual procedures. Natural language pro- cessing (NLP) offers an option for indexing and accessing these large quan- 1 The electronic society's evolution includes optical character recognition (OCR) and other processes for transforming printed text to electronic form. Also included are processes, such as imaging and sound recording, for transforming and recording nonprint electronic manifestations, but this article focuses on electronic text. -
FTS in Database
Full-Text Search in PostgreSQL Oleg Bartunov Moscow Univiversity PostgreSQL Globall DDevelolopment Group FTFTSS iinn DataDatabbaasese • Full-text search – Find documents, which satisfy query – return results in some order (opt.) • Requirements to FTS – Full integration with PostgreSQL • transaction support • concurrency and recovery • online index – Linguistic support – Flexibility – Scalability PGCon 2007, Ottawa, May 2007 Full-Text Search in PostgreSQL Oleg Bartunov WWhhaatt isis aa DocumeDocumenntt ?? • Arbitrary textual attribute • Combination of textual attributes • Should have unique id id --- id Title Did -- ------ ---- Author Abstract Aid --------- ----------- ---- Keywords ------------- Body Title || Abstract || Keywords || Body || Author PGCon 2007, Ottawa, May 2007 Full-Text Search in PostgreSQL Oleg Bartunov TTexextt SeSeararchch OpOpeeraratotorrss • Traditional FTS operators for textual attributes ~, ~*, LIKE, ILIKE Problems – No linguistic support, no stop-words – No ranking – Slow, no index support. Documents should be scanned every time. PGCon 2007, Ottawa, May 2007 Full-Text Search in PostgreSQL Oleg Bartunov FTFTSS iinn PostgrePostgreSQSQLL =# select 'a fat cat sat on a mat and ate a fat rat'::tsvector @@ 'cat & rat':: tsquery; – tsvector – storage for document, optimized for search • sorted array of lexemes • positional information • weights information – tsquery – textual data type for query • Boolean operators - & | ! () – FTS operator tsvector @@ tsquery PGCon 2007, Ottawa, May 2007 Full-Text Search in PostgreSQL -
An Association Thesaurus for Information Retrieval 1 Introduction
An Asso ciation Thesaurus for Information Retrieval Yufeng Jing and W Bruce Croft Department of Computer Science University of Massachusetts at Amherst Amherst MA jingcsumassedu croftcsumassedu Abstract Although commonly used in b oth commercial and exp erimental information retrieval systems thesauri have not demonstrated consistent b enets for retrieval p erformance and it is dicult to construct a thesaurus automatically for large text databases In this pap er an approach called PhraseFinder is prop osed to construct collectiondep e ndent asso ciation thesauri automatically using large fulltext do cument collections The asso ciation thesaurus can b e accessed through natural language queries in INQUERY an information retrieval system based on the probabilistic inference network Exp eriments are conducted in IN QUERY to evaluate dierent typ es of asso ciation thesauri and thesauri constructed for a variety of collections Intro duction A thesaurus is a set of items phrases or words plus a set of relations b etween these items Although thesauri are commonly used in b oth commercial and exp erimental IR systems ex p eriments have shown inconsistent eects on retrieval eectiveness and there is a lack of viable approaches for constructing a thesaurus automatically There are three basic issues related to thesauri in IR as follows These issues should each b e addressed separately in order to improve retrieval eectiveness Construction There are two typ es of thesauri manual and automatic The fo cus of this pap er is on how to construct a -
214310991.Pdf
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Governors State University Governors State University OPUS Open Portal to University Scholarship All Capstone Projects Student Capstone Projects Fall 2015 A Survey to Fix the Threshold and Implementation for Detecting Duplicate Web Documents Manojreddy Bhimireddy Governors State University Krishna Pavan Gandi Governors State University Reuven Hicks Governors State University Bhargav Roy Veeramachaneni Governors State University Follow this and additional works at: http://opus.govst.edu/capstones Part of the Software Engineering Commons Recommended Citation Bhimireddy, Manojreddy; Gandi, Krishna Pavan; Hicks, Reuven; and Veeramachaneni, Bhargav Roy, "A Survey to Fix the Threshold and Implementation for Detecting Duplicate Web Documents" (2015). All Capstone Projects. 155. http://opus.govst.edu/capstones/155 For more information about the academic degree, extended learning, and certificate programs of Governors State University, go to http://www.govst.edu/Academics/Degree_Programs_and_Certifications/ Visit the Governors State Computer Science Department This Project Summary is brought to you for free and open access by the Student Capstone Projects at OPUS Open Portal to University Scholarship. It has been accepted for inclusion in All Capstone Projects by an authorized administrator of OPUS Open Portal to University Scholarship. For more information, please contact [email protected]. Table of Contents 1 Project Description ............................................................................................................................