Special Issue on Natural Language Processing 2014

Copyright Statement: This is an open access publication licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

View Full Issue

Paper 1: Representation of a Sentence using a Polar Fuzzy Neutrosophic Semantic Net

Abstract: A semantic net can be used to represent a sentence. A sentence in a language contains semantics which are polar in nature, that is, semantics which are positive, neutral and negative. Neutrosophy is a relatively new field of science which can be used to mathematically represent triads of concepts. These triads include truth, indeterminacy and falsehood, and so also positivity, neutrality and negativity. Thus a conventional semantic net has been extended in this paper using neutrosophy into a Polar Fuzzy Neutrosophic Semantic Net. A Polar Fuzzy Neutrosophic Semantic Net has been implemented in MATLAB and has been used to illustrate a polar sentence in English language. The paper demonstrates a method for the representation of polarity in a computer’s memory. Thus, polar concepts can be applied to imbibe a machine such as a robot, with emotions, making machine emotion representation possible.

Author 1: Sachin Lakra
Author 2: T. V. Prasad
Author 3: G. Ramakrishna

Keywords: semantic net; polarity; neutrosophy; polar fuzzy neutrosophic semantic net;NLP

PDF

Paper 2: Key Issues in Vowel Based Splitting of Telugu Bigrams

Abstract: Splitting of compound Telugu words into its components or root words is one of the important, tedious and yet inaccurate tasks of Natural Language Processing (NLP). Except in few special cases, at least one vowel is necessarily involved in Telugu conjunctions. In the result, vowels are often repeated as they are or are converted into other vowels or consonants. This paper describes issues involved in vowel based splitting of a Telugu bigram into proper root words using Telugu grammar conjunction (‘sandhi’) rules for MT.

Author 1: T. Kameswara Rao
Author 2: Dr. T. V.Prasad

Keywords: Telugu word splitting; vowel based splitting; compound word splitting; bigrams; trigrams; n-grams; NLP

PDF

Paper 3: Solving Semantic Problem of Phrases in NLP Using Universal Networking Language (UNL)

Abstract: This paper largely deals with the Semantic problem and generation of semantic relations, which are difficult problems in the field of natural language processing. In this work we looked at it through the knowledge based perspective and language phenomena in terms of rules and dictionary features. The work is more focused on solving the problems of Bangla sentences, thereby improving the accuracy of analysis process. The problem needs, particularly, a knowledge intensive solution. We have used insights from linguistics, towards solving this problem. Also, the usefulness of automatic extraction of features for words in the dictionary becomes evident through the work.

Author 1: M. F Mridha
Author 2: Aloke Kumar Saha
Author 3: Jugal Krishna Das

Keywords: Syntax and Semantic analysis; Bangla Root Word; Morphology and UNL; NLP

PDF

Paper 4: Analyzing Opinions and Argumentation in News Editorials and Op-Eds

Abstract: Analyzing opinions and arguments in news editorials and op-eds is an interesting and a challenging task. The challenges lie in multiple levels – the text has to be analyzed in the discourse level (paragraphs and above) and also in the lower levels (sentence, phrase and word levels). The abundance of implicit opinions involving sarcasm, irony and biases adds further complexity to the task. The available methods and techniques on sentiment analysis and opinion mining are still much focused in the lower levels, i.e., up to the sentence level. However, the given task requires the application of the concepts from a number of closely related sub-disciplines – Sentiment Analysis, Argumentation Theory, Discourse Analysis, Computational Linguistics, Logic and Reasoning etc. The primary argument of this paper is that partial solutions to the problem can be achieved by developing linguistic resources and using them for automatically annotating the texts for opinions and arguments. This paper discusses the ongoing efforts in the development of linguistic resources for annotating opinionated texts, which are useful in the analysis of opinions and arguments in news editorials and op-eds.

Author 1: Bal Krishna Bal

Keywords: editorials; opinions; arguments; persuasion; sentiment analysis, annotation; NLP

PDF

Paper 5: Automating the Shaping of Metadata Extracted from a Company Website with Open Source Tools

Abstract: As part of a market analysis process, the objective was to automate the task of identifying the activities and skills of a collection of enterprises, namely Belgian and French open source companies. In order to avoid manual annotation through visual analysis of the websites’ content, a tool chain was developed to collect the content of websites and extract the important terms. Standard software libraries were identified, allowing to clean up HTML documents and to perform the part-of-speech tagging process used for extracting terminology. This procedure is supplemented by the extraction and the recognition of named entities. The terms extracted in the HTML pages of a company website were then merged and filtered and a circular tags cloud was generated. This presentation facilitates the identification of important terms, commonly referred to as activities and technologies supported by the company. Several changes are planned for this prototype, including, in particular, the extension to the texts in French, the association of extracted terms to the vocabulary of a classification scheme and the automatic generation of dashboards to facilitate the monitoring of the evolution of the industrial sector.

Author 1: Dr Ir Robert VISEUR

Keywords: terminology extraction; named entities; NLP; tag cloud; market analysis

PDF

Paper 6: Towards the Design of a Textile Chemical Ontology

Abstract: The main goal of this paper is to present the initial version of a Textile Chemical Ontology, to be used by textile professionals with the purpose of conceptualising and representing the banned and harmful chemical substances that are forbidden in this domain. After analysing different methodologies and determining that “Methontology” is the most appropriate for the purposes, this methodology is explored and applied to the domain. In this manner, an initial set of concepts are defined, together with their hierarchy and the relationships between them. This paper shows the benefits of using the ontology through a real use case in the context of Information Retrieval. The potentiality of the proposed ontology in this preliminary evaluation encourages extending the ontology with a higher number of concepts and relationships, and validating it within other Natural Language Processing applications.

Author 1: Carolina Prieto Ferrero
Author 2: Elena Lloret
Author 3: Manuel Palomar

Keywords: Ontology; Chemical Textile; Chemical Ontology; Textile Ontology; Chemical Textile Ontology; NLP

PDF

Paper 7: A Simple Strategy to Start Domain Ontology from Scratch

Abstract: Aiming the usage of Domain Ontology as an educational tool for neophyte students and focusing in a fast and easy way to start Domain Ontology from scratch, the semantics are set aside to identify contexts of concepts (terms) to build the ontology. Text Mining, Link Analysis and Graph Analysis create an abstract rough sketch of interactions between terms. This first rough sketch is presented to the expert providing insights into and inspires him to inform or communicate knowledge, through assertive sentences. Those assertive sentences subsidize the creation of the ontology. A web prototype tool to visualize the ontology and retrieve book contents is also presented.

Author 1: Ivo Wolff Gersberg
Author 2: Nelson F. F. Ebecken

Keywords: domain ontology; contextual approach; ontology; NLP

PDF

Paper 8: An Effective Reasoning Algorithm for Question Answering System

Abstract: Knowledge representation (KR) is the most desirable area of research to make the system intelligent. Today is the era of knowledge that requires articulations, semantic, syntax etc. These requirements, forced to design a general system which is applicable to represent declarative as well as procedural knowledge. Without effective inference/reasoning mechanism, the strength and utility of knowledge representation technique fulfill the partial requirement for an intelligent system. The objective of this research work is to present the effective/ appropriate knowledge representation technique for representing the general knowledge and a reasoning algorithm for Question Answering system (QAS) work as story reader, so that appropriate knowledge can be infer from the system. The architecture of knowledge representation system is capable to integrate different type of knowledge and it is cost effective also.

Author 1: Poonam Tanwar
Author 2: Dr. T. V. Prasad
Author 3: Dr. Kamlesh Datta

Keywords: Knowledge Representation (KR); Semantic Net; Script; Reasoning; QAS; NLP

PDF

Paper 9: A Survey of Automated Text Simplification

Abstract: Text simplification modifies syntax and lexicon to improve the understandability of language for an end user. This survey identifies and classifies simplification research within the period 1998-2013. Simplification can be used for many applications, including: Second language learners, preprocessing in pipelines and assistive technology. There are many approaches to the simplification task, including: lexical, syntactic, statistical machine translation and hybrid techniques. This survey also explores the current challenges which this field faces. Text simplification is a non-trivial task which is rapidly growing into its own field. This survey gives an overview of contemporary research whilst taking into account the history that has brought text simplification to its current state.

Author 1: Matthew Shardlow

Keywords: Text Simplification, Lexical Simplification, Syntactic; NLP Simplification

PDF