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In this paper, we describe an approach for extracting named entities from Arabic texts. Arabic language is hard to process since its characteristics that influence, even, the NE extraction. For our case, we consider that the named entities extraction can be assimilated to a typical classification problem. Indeed, this extraction consists of searching for text portions that can be classified in a NE...
Keyphrases extraction has a considerable importance in many applications such as search engine optimization, clustering, summarization, and sentiment analysis. The importance of keyphrases comes from the semantic meaning they provide as they can be used as descriptors for the documents. In this paper we compare four approaches for extracting keyphrases from Arabic documents. The first method uses...
This paper proposes a method for adapting robot's perception to produce fuzzy vocal responses about the size of an object based on the visual attention of the robot. In a human-human interaction, the humans may use vocal responses, which have qualitative terms such as "small", "large" etc. The actual quantitative meaning of those terms depends on spatial arrangement of the environment...
One of the key challenges in software projects is the efficient allocation of human resources to software development tasks. To achieve this challenge, the proper human resource evaluation and selection is an important step. In this paper we present a fuzzy linguistic approach that utilizes 2-tuple fuzzy linguistic terms and supports the selection of suitable human resources based on their skills...
In this paper, we discuss application of special soft computing methods, namely the fuzzy natural logic and fuzzy transform, to the problem of mining information from time series. The mined information is formulated in natural language. We discuss the following applications: reduction of size of time series, extraction of its trend-cycle, linguistic characterization of its future course and forecast...
This paper presents a new dynamic model for fuzzy consensus that uses randomness in the modeling of the individual process iterations, this leads to singular (different) consensus process paths. The imprecision of the resulting different consensus results is captured by a simple process to form an overall consensus result from the distribution of the singular consensus results. The introduction of...
The increased usage of Twitter as a medium for reporting news and sharing information between people has caught the attention of researchers from different disciplines. One of the research directions is the analysis of online information from the perspective of its credibility. This paper aims to assess and analyze the credibility of tweets in Arabic language. In order to achieve the stated goal,...
Electronic detection of linguistic negation in free text is a challenging need for many text handling applications including sentiment analysis. Our system uses online news archives from two different resources namely NDTV and The Hindu to predict the scope of negation in the text. In this paper, our main target was on determining the scope of negation in news articles for two political parties namely...
The research context of this paper further expands the probable understanding on the use of corrective feedbacks among online English teachers and their underlying cognition given the computer-mediated communication context of their online class discourse. By installing new probable component and contextual computer-mediated communication features on teacher cognition in corrective feedbacks research,...
Affective interaction is a new emerging area of interest for interaction designers. This research explores the potential of our hybrid approach that relies on both, lexical and machine learning techniques for detection of Ekman's six emotional categories in user's text. The initial results of the performance evaluation of the proposed hybrid approach are encouraging and comparable to related research...
In the last decade, Online Analytical Processing (OLAP) has taken an increasingly important role in Business Intelligence. Approaches, solutions and tools have been provided for both databases and data warehouses, which focus mainly on numerical data. These solutions are not suitable for textual data. Because of the fast growing of this type of data, there is a need for new approaches that take into...
Component-based modeling and simulation brings a number of advantages to large-scale, complex simulation. How to achieve higher level composability in model composition proves to be more and more important. Based on pragmatic composability analysis, an Extended Finite State Machine-based Context-Aware simulation component formal description was proposed, including the context constraints and conditions...
In machine translation the co reference resolution has important significance. Without correct co-reference any translation has wrong interpretation. In this paper we investigated the type of antecedent for Hindi. We discussed the five values of this feature of antecedent. We analyzed 165 news items of Ranchi Express from EMILEE corpus of plain text. It consist 2382 sentences. Eight file of dialogue...
Question Analysis is an important task in Question Answering Systems (QAS). It consists generally in identifying the semantic type of the question and extracting the main focus of the question. The goal is to better specify the required information by the question. In this context and as part of a framework aiming to implement an Arabic opinion QAS for political debates, this paper addresses the problem...
Assigning the appropriate grammatical category to a word given a context is very important step in major areas of natural language processing. A limited numbers of Part of Speech Taggers currently exist for Arabic. These taggers mainly adopt tagsets that were developed for languages such as English. In this paper we present an effort of proposing a revised categories for Arabic POS tags that would...
The internet has evolved from an informational space to a significant communication space, a worldwide social network by which millions of opinions are expressed daily with no sociological, psychological, temporal or spatial constraint. The content analysis of these opinions allows us to identify and then categorize the sentiments they carry. In this article, we will attempt to present the state of...
Component-based modeling and simulation brings a number of advantages to large-scale, complex simulation. How to achieve higher level composability in model composition proves to be more and more important. Based on pragmatic composability analysis, an Extended Finite State Machine-based Context-Aware simulation component formal description was proposed, including the context constraints and conditions...
We present here a data mining approach for part-of-speech (POS) tagging, an important Natural language processing (NLP) classification task. We propose a semi-supervised associative classification method for POS tagging. Existing methods for building POS taggers require extensive domain and linguistic knowledge and resources. Our method uses a combination of a small POS tagged corpus and untagged...
This paper presents the application of knowledge-based epistemology of engineering to the understandings of the engineering design process. This work aims to extend discussion on Philosophy of Engineering into its impact on our understanding of engineering design. The question this paper aims to address is how a knowledge-based philosophy of engineering supports the distinctive challenges in distinguishing...
Corpora have become bigger, better and more numerous, and their interfaces are quicker, simpler and freely available for use on any computer. At the same time, user manuals and teaching materials have been created to support the technology. The technological and pedagogical aspects of corpus-based language learning are equally important, but the previous research has been weighted towards the creation...
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