Search results for: Mouheb Mehdoui
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3

Search results for: Mouheb Mehdoui

3 Unlocking the Potential of Short Texts with Semantic Enrichment, Disambiguation Techniques, and Context Fusion

Authors: Mouheb Mehdoui, Amel Fraisse, Mounir Zrigui

Abstract:

This paper explores the potential of short texts through semantic enrichment and disambiguation techniques. By employing context fusion, we aim to enhance the comprehension and utility of concise textual information. The methodologies utilized are grounded in recent advancements in natural language processing, which allow for a deeper understanding of semantics within limited text formats. Specifically, topic classification is employed to understand the context of the sentence and assess the relevance of added expressions. Additionally, word sense disambiguation is used to clarify unclear words, replacing them with more precise terms. The implications of this research extend to various applications, including information retrieval and knowledge representation. Ultimately, this work highlights the importance of refining short text processing techniques to unlock their full potential in real-world applications.

Keywords: information traffic, text summarization, word-sense disambiguation, semantic enrichment, ambiguity resolution, short text enhancement, information retrieval, contextual understanding, natural language processing, ambiguity

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2 Leveraging Large Language Models to Build a Cutting-Edge French Word Sense Disambiguation Corpus

Authors: Mouheb Mehdoui, Amel Fraisse, Mounir Zrigui

Abstract:

With the increasing amount of data circulating over the Web, there is a growing need to develop and deploy tools aimed at unraveling semantic nuances within text or sentences. The challenges in extracting precise meanings arise from the complexity of natural language, while words usually have multiple interpretations depending on the context. The challenge of precisely interpreting words within a given context is what the task of Word Sense Disambiguation meets. It is a very old domain within the area of Natural Language Processing aimed at determining a word’s meaning that it is going to carry in a particular context, hence increasing the correctness of applications processing the language. Numerous linguistic resources are accessible online, including WordNet, thesauri, and dictionaries, enabling exploration of diverse contextual meanings. However, several limitations persist. These include the scarcity of resources for certain languages, a limited number of examples within corpora, and the challenge of accurately detecting the topic or context covered by text, which significantly impacts word sense disambiguation. This paper will discuss the different approaches to WSD and review corpora available for this task. We will contrast these approaches, highlighting the limitations, which will allow us to build a corpus in French, targeted for WSD.

Keywords: semantic enrichment, disambiguation, context fusion, natural language processing, multilingual applications

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1 Effect of the Fluid Temperature on the Crude Oil Fouling in the Heat Exchangers of Algiers Refinery

Authors: Rima Harche, Abdelkader Mouheb

Abstract:

The Algiers refinery as all the other refineries always suffers from the problem of stopping of the tubes of heat exchanger. For that a study experimental of this phenomenon was undertaken in site on the cell of heat exchangers E101 (E101 CBA and E101 EDF) intended for the heating of the crude before its fractionation, which are exposed to the problem of the fouling on the side tubes exchangers. It is of tube-calenders type with head floating. Each cell is made up of three heat exchangers, laid out in series.

Keywords: fouling, fluid temperatue , oil, tubular heat exchanger, fouling resistance, modeling, heat transfer coefficient

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