Section: New Results

CominWeb project of the Labex CominLabs

Jean Hany and Albert Benveniste (together with William Dedzoe) were involved in this project.

CominWeb is a project supported by the Labex CominLabs since 2013. Its original objective was to equip CominLabs with Web infrastructures, tools, and services, that would allow to run the scientific activity of the Labex in an innovative way. Based on a study of the population of the CominLabs researchers, performed in year 2014-15 by the teams of CominLabs involved in social sciences, several services were investigated and prototyped. A short trial addressed the automatic generation of a scientific activity report, for a CominLabs project, from the material available from the publications ot the project team. This was suspended because such a service was not considered very useful by the community. A second trial (nicknamed “NSA”) consisted in monitoring the flows of email exchanges addressed to aliases of the CominLabs projects, with the objective of classifying the mails into: meeting announcements, mails with attachments of interest, and other mails. This would give to the CominLabs head a view on the project's activities without asking for any specific contribution from the researchers. This was more interesting. Still, a difficulty was that researchers did not use the project aliases so much. For priority issues, this development was also suspended.

The main result of this project is thus the service called LookinLabs, deployed in two different versions: http://lookinlabs4halinria.cominlabs.ueb.eu/ and http://www.lookinlabs.cominlabs.ueb.eu/. The former is a more advanced version of LookinLabs, developed for the whole Inria community, by exploiting the HAL publication archive. LookinLabs for HAL-Inria allows the user to find, among teams/individuals/publications taken from all the Inria teams, those best matching a query consisting of a list of keywords or a short text. The tool exploits, as data, HAL-Inria archives, in combination with the Inria Activity reports (the Raweb), and the internal data base of Inria teams called BASTRI. Active teams/individuals are shown in boldface. Teams/individuals shown in gray are no longer active at Inria. If team TEAM0 is no longer active, the mention: TEAM0 $\to$ (TEAM1,TEAM2) indicates follow-up active teams, if any. In LookinLabs, no ontology is used. No data need to be manually entered (besides the users’ queries). The tool uses Elasticsearch (https://www.elastic.co/fr/products/elasticsearch) as its core algorithm. This means that the matching is based on a distance between the query and the set of data attached, in HAL, to each team/individual/publication. Ranking is performed accordingly. Explanations are given for each returned item. Correlation graphs are given, allowing to navigate through teams or individuals that share common interests (they may or may not be co-authors).

LookinLabs is deployed in two versions. LookinLabs4HALInria is the one we just described. The other version is in operation since 2016 and addresses the scientific community of CominLabs researchers. The data used are up to 10 standard bibliographical data bases (Dblp, IEEE Explore, Arxiv, HAL, and more) for which links have been collected from the researchers (this was the only data they were asked for). Results are returned in the form of individuals and publications, not teams.