Bilel Gargouri

ISO standard modeling of a large Arabic dictionary

In this paper, we address the problem of the large coverage dictionaries of Arabic language usable both for direct human reading and automatic Natural Language Processing. For these purposes, we propose a normalized and implemented modeling, based on Lexical Markup Framework (LMF-ISO 24613) and Data Registry Category (DCR-ISO 12620), which allows a stable and well-defined interoperability of lexical resources through a unification of the linguistic concepts. Starting from the features of the Arabic language, and due to the fact that a large range of details and refinements need to be described specifically for Arabic, we follow a finely structuring strategy. Besides its richness in morphology, syntax and semantics knowledge, our model includes all the Arabic morphological patterns to generate the inflected forms from a given lemma and highlights the syntactic–semantic relations. In addition, an appropriate codification has been designed for the management of all types of relationships among lexical entries and their related knowledge. According to this model, a dictionary named El Madar 1 has been built and is now publicly available on line. The data are managed by a user-friendly Web-based lexicographical workstation. This work has not been done in isolation, but is the result of a collaborative effort by an international team mainly within the ISO network during a period of eight years.

Supervised Learning to Measure the Semantic Similarity Between Arabic Sentences

Many methods for measuring the semantic similarity between sentences have been proposed, particularly for English. These methods are considered restrictive as they usually do not take into account some semantic and syntactic-semantic knowledge like semantic predicate, thematic role and semantic class. Measuring the semantic similarity between sentences in Arabic is particularly a challenging task because of the complex linguistic structure of the Arabic language and given the lack of electronic resources such as syntactic-semantic knowledge and annotated corpora.

Using Standardized Lexical Semantic Knowledge to Measure Similarity

The issue of sentence semantic similarity is important and essential to many applications of Natural Language Processing. This issue was treated in some frameworks dealing with the similarity between short texts especially with the similarity between sentence pairs. However, the semantic component was paradoxically weak in the proposed methods. In order to address this weakness, we propose in this paper a new method to estimate the semantic sentence similarity based on the LMF ISO-24613 standard. Indeed, LMF provides a fine structure and incorporates an abundance of lexical knowledge which is interconnected together, notably sense knowledge such as semantic predicates, semantic classes, thematic roles and various sense relations. Our method proved to be effective through the applications carried out on the Arabic language. The main reason behind this choice is that an Arabic dictionary which conforms to the LMF standard is at hand within our research team. Experiments on a set of selected sentence pairs demonstrate that the proposed method provides a similarity measure that coincides with human intuition.

Domain Ontology Enrichment Based on the Semantic Component of LMF-Standardized Dictionaries

This paper proposes an approach for automatic domain ontology enrichment based on the semantic component of Lexical Markup Framework (LMF, ISO 24613)-standardized dictionaries. The originality of this research work lies in the use of simple and regularly-structured textual fields disseminated in the definitions and examples of lexical entries, thus facilitating the extraction of concepts and relations candidates. It also lies in exploiting the semantic component of the LMF dictionary in order to guide the extraction of further knowledge from the adopted source. Along with addressing the quality issue which is of a major importance in ontology engineering, the proposed approach has been implemented in a rule-based system, relying on lexicosyntactic patterns for ontology items extraction and applied to a case study in the field of astronomy. The experiment has been carried out on the Arabic language, whose choice is explained both by the great deficiency of research work on the Arabic ontology development and the availability within our research team of an LMF-standardized Arabic dictionary.

An Ontology-Based Approach for Linguistic Web Service Description

This paper proposes an ontology-based approach for the description of Linguistic Web Services (Ling WS). This approach provides a rich semantic description using two kinds of ontology. The first one covers both the OWL-S ontology for the Functional properties and an extension of this later for the Non-Functional NLP properties and their relationships. The second one is an NLP domain ontology based on ISO standards to semantically annotate the Ling WS properties.

Semantic-based approach to improve the description and the discovery of Linguistic Web Services

This paper deals with the description and the discovery of Web Services in the linguistic information system. The previous studies have proved the lack of semantics within the descriptions of the linguistic Web Services (LingWS for short) which negatively affects the quality of their discovery. In order to overcome this problem, we propose to integrate the nonfunctional linguistic properties and their relationships inside the advertisements and to semantically annotate the several elements of the LingWS descriptions. Thus, we suggest an extension of OWL-S that promotes such a proposal. Moreover, we ensure the semantic annotation through a linguistic domain ontology that we have developed using the ISO standards of linguistic data categories (ISO 12620). This proposal is consolidated with the implementation of an editor called OWL-LingS (stands for OWL for Linguistic Services). As for the discovery task, we have extended the OWLS-MX hybrid matchmaker by integrating the nonfunctional linguistic properties within its matching algorithm. The obtained matchmaker, called OWL-LingS-MX, promotes the creation of the user requests according to the extended description of LingWS. The performance of OWL-LingS-MX matchmaker is shown through a comparison with three famous OWL-S matchmakers on the same computer. These systems are iSeM, OWLSM, and OWLS-MX.

Towards the reuse of lingware systems: a proposed approach with a practical experiment

We are going to present in this document a generic approach for lingware systems reuse. This approach is based on reverse engineering technique in order to wrap up an existing lingware system with web services. This approach permits the reuse of lingware systems regardless of programming languages, development environments and the structures of linguistic resources. In order to preserve the interoperability between the reused lingware systems, the proposed approach performs the unification and the standardization of exchanged linguistic data using the Natural Language Processing (NLP) standards and consensus. Doing so, we facilitate the integration and the composition of lingware services in order to create a new application that treats several linguistic levels. In order to consolidate the given approach, we developed the LIngware Reuse Environment (LIRE). A practical experiment was carried out using LIRE environment on an automatic application summary of Arabic texts.

A formal approach to lingware development

This paper has two purposes. First, it presents a formal approach for the specification and development of lingware. This approach is based on the integration of the main existent formalisms for describing linguistic knowledge (i.e., Formal Grammars, Unification Grammars, HPSG, etc .) on the one hand, and the integration of data and processing on the other one. In this way, a specification of an application treating natural language includes all related aspects (linguistic and processing) in a unified framework. This approach promotes the reuse of proved correct specifications ( linguistic knowledge specifications, modules and subsystems).

Enhancing the sentence similarity measure by semantic and syntactico-semantic knowledge

The measure of sentence similarity is useful in various research fields, such as artificial intelligence, knowledge management, and information retrieval. Several methods have been proposed to measure the sentence similarity based on syntactic and/or semantic knowledge. Most proposals are evaluated on English sentences where the accuracy can decrease when these proposals are applied to other languages. Moreover, the results of these methods are unsatisfactory, as much relevant semantic knowledge, such as semantic class, thematic role and syntactico-semantic knowledge like the semantic predicates, are not taken into account. We must acknowledge that this kind of knowledge is rare in most of the lexical resources. Recently, the International Organization for Standardization (ISO) has published the Lexical Markup Framework (LMF) ISO-24613 norm for the development of lexical resources. This norm provides, for each meaning of a lexical entry, all the semantic and syntactico-semantic knowledge in a fine structure. Profiting from the availability of LMF-standardized dictionaries, we propose, in this paper, a generic method that enhances the measure of sentence similarity by applying semantic and syntactico-semantic knowledge. An experiment was carried out on Arabic, as this language is processed within our research team and an LMF-standardized Arabic dictionary is at hand where the semantic and the syntactico-semantic knowledge are accessible and well structured. Moreover, the experiments yielded better results, showing a high correlation with human ratings.

Collaborative Enrichment of Electronic Dictionaries Standardized-LMF

The collaborative enrichment is a new tendency in constructing resources, notably electronic dictionaries. This approach is considered very efficient for resources weakly structured. In this paper, we deal with applying the collaborative enrichment for electronic dictionaries standardized according to LMF-ISO 24613. The models of such dictionaries are complex and finely structured. The purpose of the paper is, on the one hand, to expose the challenges related to this framework and, in the second hand, to propose practical solutions based on an appropriate approach. This approach ensures the properties of completeness, consistency and non-redundancy of lexical data. In order to illustrate the proposed approach, we describe the experimentation carried out on a standardized Arabic dictionary.