Mathieu Mangeot

The PAPILLON project: cooperatively building a multilingual lexical data-base to derive open source dictionaries & lexicons

The PAPILLON project aims at creating a cooperative, free, permanent, web-oriented and personalizable environment for the development and the consultation of a multilingual lexical database. The initial motivation is the lack of dictionaries, both for humans and machines, between French and many Asian languages. In particular, although there are large F-J paper usage dictionaries, they are usable only by Japanese literates, as they never contain both original (kanji/kana) and romaji writing. This applies as well to Thai, Vietnamese, Lao, etc.

Constructing Multilingual Preterminological Graphs using various online-community resources

We are describe the concept of dedicated Multilingual Preterminological Graphs MPGs, and some automatic approaches for constructing them by analyzing the behavior of online community users. A Multilingual Preterminological Graph is a special lexical resource that contains massive amount of terms related to a special domain, and can be used as raw material to later build a standardized terminological repository. Building such a graph is difficult using traditional approaches, as it needs huge efforts by domain specialists and terminologists. In our approach, we build such a graph by analyzing the access log files of the website of the community, and by finding the important terms that have been used to search in that website, and their association with each other. We aim at making this graph as a seed repository so multilingual volunteers can contribute. We are experimenting this approach with the Digital Silk Road Project. We have used its access log files since its beginning in 2003, and obtained an initial graph of around 116000 terms. As an application, we used this graph to obtain a preterminological multilingual database that is serving a CLIR system for the DSR project.

Building specialized multilingual lexical graphs using community resources

We are describing methods for compiling domain-dedicated multilingual terminological data from various resources. We focus on collecting data from online community users as a main source, therefore, our approach depends on acquiring contributions from volunteers (explicit approach), and it depends on analyzing users behaviors to extract interesting patterns and facts (implicit approach). As a generic repository that can handle the collected multilingual terminological data, we are describing the concept of dedicated Multilingual Preterminological Graphs MPGs, and some automatic approaches for constructing them by analyzing the behavior of online community users. A Multilingual Preterminological Graph is a special lexical resource that contains massive amount of terms related to a special domain. We call it preterminological, because it is a raw material that can be used to build a standardized terminological repository. Building such a graph is difficult using traditional approaches, as it needs huge efforts by domain specialists and terminologists. In our approach, we build such a graph by analyzing the access log files of the website of the community, and by finding the important terms that have been used to search in that website, and their association with each other. We aim at making this graph as a seed repository so multilingual volunteers can contribute. We are experimenting this approach with the Digital Silk Road Project. We have used its access log files since its beginning in 2003, and obtained an initial graph of around 116000 terms. As an application, we used this graph to obtain a preter-minological multilingual database that is serving a CLIR system for the DSR project.

Jibiki-LINKS: a tool between traditional dictionaries and lexical networks for modelling lexical resources

Between simple electronic dictionaries such as the TLFi (computerized French Language Treasure) 1 and lexical networks like WordNet 2 (Diller et al., 1990; Vossen, 1998), the lexical databases are growing at high speed. Our work is about the addition of rich links to lexical databases, in the context of the parallel development of lexical networks. Current research on management tools for lexical databases is strongly influenced by the field of massive data (big data) and by the Web of data (linked data). In lexical networks, one can build and use arbitrary links, but possible queries cannot model all the usual interactions with lexicographers-developers and users, that are needed, and derive from the paper world. Our work aims to find a solution that allows for the main advantages of lexical networks, while providing the equivalent of paper dictionaries by doing the lexicographic work in lexical DBs.