Typology of Data Inputs Imperfection in Collective Memory Model

International audienceHandling imperfect data inputs in applications for collective and individual memory is a crucial issue in shaping an updated and unprecedented view of it. In the literature, several typologies of data imperfections are proposed. However, these typologies cannot be applied to this context due to its particular specificities. In this paper, we propose a typology of imperfection for data entered by users in the applications for collective and individual memory. It includes nine direct imperfections types and four indirect ones. The direct ones are generated directly from the data inputs e.g., uncertainty and imprecision. The indirect imperfection types are generated from the direct ones, e.g., inconsistency is generated from uncertainty. We finish by representing an example of imprecise temporal data in the Collective Memo Onto (CMO) ontology

Handling Temporal Data Imperfections in OWL 2 - Application to Collective Memory Data Entries

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le d6veloppement

l'utilisation des m6thodes formelles pou

An Ontology based Smart Management of Linguistic Knowledge

International audienceNatural language processing provides a very significant contribution to various application areas such as multilingual big data, information retrieval, data integration and multilingual web. However, handling linguistic knowledge to develop such lingware applications is a crucial issue, especially for linguistic novice users. To deal with this issue, a "smart" linguistic knowledge management may help the users to understand the meaning, scope and especially the use of related techniques and algorithms. In this paper, (1) we propose a semantic processing of linguistic knowledge based on a multilingual linguistic domain ontology, called LingOnto. Compared to related work, LingOnto does not only handles linguistic data, but also linguistic processing functionalities and linguistic processing features. Besides, it allows, via a reasoning engine, inferring new linguistic knowledge and assisting in the process of proposing lingware applications. This is particularly useful for novice users, but can also provide new perspectives for the expert ones. LingOnto covers the French, English and Arabic languages. (2) We propose also an assisted user friendly ontology visualization tool called LingGraph. It facilitates the interaction with LingOnto. It offers an easy to use interface for users not familiar with ontologies. It is based on a SPARQL pattern-based approach to allow a smart search interaction functionality to visualize only the ontological view corresponding to the user’s needs and preferences. In order to evaluate LingOnto, we apply it to a framework of identifying valid natural language processing pipelines. Finally, we give the results of the carried-out experiments

A Smart Search Functionality for a Memory Prosthesis: A Semantic Similarity-Based Approach

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An Evidence Theory-Based Approach to Handling Conflicting Temporal Data in OWL 2

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A Semantic and Smart Framework for Handling Multilingual Linguistic Knowledge: A Framework and Case Implementation

International audienceThe authors propose a semantic and smart assistance framework for handling linguistic knowledge, called LingFramework. It targets both expert and novice users. It aims to assist the user in understanding the different aspects of the linguistic domain and ease the process of proposing lingware applications. LingFramework is based on a multilingual linguistic domain ontology called LingOnto. It allows (1) representing linguistic data, linguistic processing functionalities and linguistic processing features, and (2) reasoning, via a SWRL-based reasoning engine, about the linguistic knowledge. Currently, it covers English, French, and Arabic languages. To facilitate the interaction with LingOnto, an ontology visualization tool called LingGraph is proposed. It offers an easy-to-use interface for users not familiar with ontologies. It provides a SPARQL pattern-based approach to allow a smart search interaction functionality. LingFramework is applied to assist the user in identifying valid linguistic processing pipelines related to lingware applications. The evaluation results are promising