scholarly journals Contribution to Semantic Analysis of Arabic Language

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Anis Zouaghi ◽  
Mounir Zrigui ◽  
Georges Antoniadis ◽  
Laroussi Merhbene
Keyword(s):  
Information Retrieval ◽  
Semantic Analysis ◽  
String Matching ◽  
Ambiguous Word ◽  
Arabic Language ◽  
New Approach ◽  
Matching Algorithm ◽  
Ambiguous Words ◽  
Lesk Algorithm ◽  
Context Of Use

We propose a new approach for determining the adequate sense of Arabic words. For that, we propose an algorithm based on information retrieval measures to identify the context of use that is the closest to the sentence containing the word to be disambiguated. The contexts of use represent a set of sentences that indicates a particular sense of the ambiguous word. These contexts are generated using the words that define the senses of the ambiguous words, the exact string-matching algorithm, and the corpus. We use the measures employed in the domain of information retrieval, Harman, Croft, and Okapi combined to the Lesk algorithm, to assign the correct sense of those proposed.

To improve the Recovery of an Arab Stemmer for Information Retrieval

2018 ◽  
Vol 10 (1) ◽  
pp. 25-33
Author(s):  
Khaireddine Bacha
Keyword(s):  
Information Retrieval ◽  
Error Rate ◽  
Automatic Processing ◽  
Arabic Language ◽  
Extraction Process ◽  
Finite State Automata ◽  
New Approach ◽  
Root Extraction ◽  
Finite State

The automatic processing of the Arabic language is a growing discipline, in which one sees more and more research and technologies to examine the specificities of this language and to propose tools necessary to the development of its automatic processing. The old techniques of rooting have limits that weaken the process of root extraction. In this article, the author proposes a new approach to rooting based on two finite state automata. The technique proposed is based on finite state automata in the root extraction process, with the aim of minimizing the error rate and ambiguity, usually due to the removal of the affixes. The author is currently focusing on the development and improvement of the rooting technique while trying to overcome the various problems encountered. The author is working on the compilation of a corpus of evaluation which will allow him to evaluate and compare their approach to others

BFM: a forward backward string matching algorithm with improved shifting for information retrieval

2019 ◽  
Vol 12 (2) ◽  
pp. 479-483
Author(s):  
MD. Obaidullah Al-Faruk ◽  
K. M. Akib Hussain ◽  
MD. Adnan Shahriar ◽  
Shakila Mahjabin Tonni
Keyword(s):  
Information Retrieval ◽  
String Matching ◽  
Matching Algorithm

scholarly journals Semantic based Information Retrieval System by using WSD and DICE Coefficient

2020 ◽  
pp. 274-279
Author(s):  
Prof Thwe ◽  
Thi Thi Tun ◽  
Ohnmar Aung
Keyword(s):  
Information Retrieval ◽  
Word Sense Disambiguation ◽  
Ambiguous Word ◽  
Relevant Information ◽  
Word Sense ◽  
Improve Performance ◽  
Lexical Resource ◽  
Ambiguous Words ◽  
Sense Disambiguation ◽  
Similarity Method

In many NLP applications such as machine translation, content analysis and information retrieval, word sense disambiguation (WSD) is an important technique. In the information retrieval (IR) system, ambiguous words are damaging effect on the precision of this system. In this situation, WSD process is useful for automatically identifying the correct meaning of an ambiguous word. Therefore, this system proposes the word sense disambiguation algorithm to increase the precision of the IR system. This system provides additional semantics as conceptually related words with the help of glosses to each keyword in the query by disambiguating their meanings. This system uses the WordNet as the lexical resource that encodes concepts of each term. In this system, various senses that are provided by WSD algorithm have been used as semantics for indexing the documents to improve performance of IR system. By using keyword and sense, this system retrieves the relevant information according to the Dice similarity method.

scholarly journals An XML Approach of Coding a Morphological Database for Arabic Language

2011 ◽  
Vol 2011 ◽  
pp. 1-15 ◽  
Author(s):  
Mourad Gridach ◽  
Noureddine Chenfour
Keyword(s):  
Information Retrieval ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Morphological Analysis ◽  
Semantic Analysis ◽  
Arabic Language ◽  
Syntactic Analysis ◽  
Standard Arabic ◽  
Modern Standard

We present an XML approach for the production of an Arabic morphological database for Arabic language that will be used in morphological analysis for modern standard Arabic (MSA). Optimizing the production, maintenance, and extension of morphological database is one of the crucial aspects impacting natural language processing (NLP). For Arabic language, producing a morphological database is not an easy task, because this it has some particularities such as the phenomena of agglutination and a lot of morphological ambiguity phenomenon. The method presented can be exploited by NLP applications such as syntactic analysis, semantic analysis, information retrieval, and orthographical correction.

Designing a Chat-Bot for College Information using Information Retrieval and Automatic Text Summarization Techniques

2020 ◽  
Vol 01 ◽  
Author(s):  
Radha Guha
Keyword(s):  
Information Retrieval ◽  
Language Processing ◽  
Latent Dirichlet Allocation ◽  
Semantic Analysis ◽  
Text Summarization ◽  
The Internet ◽  
Specific Domain ◽  
User Query ◽  
College Information ◽  
Chat Bot

Background:: In the era of information overload it is very difficult for a human reader to make sense of the vast information available in the internet quickly. Even for a specific domain like college or university website it may be difficult for a user to browse through all the links to get the relevant answers quickly. Objective:: In this scenario, design of a chat-bot which can answer questions related to college information and compare between colleges will be very useful and novel. Methods:: In this paper a novel conversational interface chat-bot application with information retrieval and text summariza-tion skill is designed and implemented. Firstly this chat-bot has a simple dialog skill when it can understand the user query intent, it responds from the stored collection of answers. Secondly for unknown queries, this chat-bot can search the internet and then perform text summarization using advanced techniques of natural language processing (NLP) and text mining (TM). Results:: The advancement of NLP capability of information retrieval and text summarization using machine learning tech-niques of Latent Semantic Analysis(LSI), Latent Dirichlet Allocation (LDA), Word2Vec, Global Vector (GloVe) and Tex-tRank are reviewed and compared in this paper first before implementing them for the chat-bot design. This chat-bot im-proves user experience tremendously by getting answers to specific queries concisely which takes less time than to read the entire document. Students, parents and faculty can get the answers for variety of information like admission criteria, fees, course offerings, notice board, attendance, grades, placements, faculty profile, research papers and patents etc. more effi-ciently. Conclusion:: The purpose of this paper was to follow the advancement in NLP technologies and implement them in a novel application.

Emotionality effects in ambiguous word recognition: The crucial role of the affective congruence between distinct meanings of ambiguous words

2021 ◽  
pp. 174702182199000
Author(s):  
Pilar Ferré ◽  
Juan Haro ◽  
Daniel Huete-Pérez ◽  
Isabel Fraga
Keyword(s):  
Word Processing ◽  
Reaction Times ◽  
Ambiguous Word ◽  
Semantic Ambiguity ◽  
Negative Valence ◽  
Ambiguous Words ◽  
Positive Valence ◽  
Affective Meanings ◽  
Valence Effect ◽  
Affective Word

There is substantial evidence that affectively charged words (e.g., party or gun) are processed differently from neutral words (e.g., pen), although there are also inconsistent findings in the field. Some lexical or semantic variables might explain such inconsistencies, due to the possible modulation of affective word processing by these variables. The aim of the present study was to examine the extent to which affective word processing is modulated by semantic ambiguity. We conducted a large lexical decision study including semantically ambiguous words (e.g., cataract) and semantically unambiguous words (e.g., terrorism), analysing the extent to which reaction times (RTs) were influenced by their affective properties. The findings revealed a valence effect in which positive valence made RTs faster, whereas negative valence slowed them. The valence effect diminished as the semantic ambiguity of words increased. This decrease did not affect all ambiguous words, but was observed mainly in ambiguous words with incongruent affective meanings. These results highlight the need to consider the affective properties of the distinct meanings of ambiguous words in research on affective word processing.

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