Research

3rd funding period

Semantic Information Retrieval (SIR) project systematically investigates the semantic and lexical relationships between words and concepts and its usefulness in information retrieval (IR) process.

Using a variety of lexical and semantic knowledge sources such as WordNet, GermaNet, and Wikipedia, the first and second phases of the project have investigated semantic relatedness measures in monolingual settings.

The third phase of SIR project builds upon the successful outcomes of the previous phrases, with focus on the development of the following aspects:

1. Large-scale word sense disambiguated multilingual lexical semantic resource
2. Novel semantic approaches to cross-lingual IR (CLIR)

In general, IR approaches utilizing keyword matching techniques suffer “term mismatch” or “vocabulary gap” problem, because mere lookup of surface word forms fails to capture the semantic meanings expressed in users’ query. The task becomes even more difficult when cross-lingual information need is involved (e.g. search for English documents with a query in German).

The goals of this project are as follows:

1. Large-scale word sense disambiguated multilingual lexical semantic resource
   • Merge collaboratively created resources and existing lexical semantic resources into a single large-scale translation resource
2. Novel semantic approaches to cross-lingual IR (CLIR)
• Improve over the state-of-the-art CLIR performance
• Participate in the international benchmarking competitions

Our approach to achieve the above mentioned goals is as follows:

1. Large-scale word sense disambiguated multilingual lexical semantic resource
   • Extract word sense disambiguated translations from the large-scale collaboratively created resources such as Wikipedia and Wiktionary
   • Automatically align this with existing knowledge bases such as WordNet, GermaNet, and EuroWordNet at the word sense level
2. Novel semantic approaches to cross-lingual IR (CLIR)
• Train statistical translation models from word sense disambiguated translation resource
• Develop new cross-language Explicit Semantic Analysis (ESA) approaches and integrate them into CLIR models

The Division of Computational Linguistics at the University of Tübingen is co-applicant of the SIR project. Their research focus is to further extend GermaNet with (i) additional synsets and their definitions, and (ii) additional Interlingual Index (ILI) entries for interconnecting senses in multilingual knowledge bases.

This project is funded by Deutsche Forschungsgemeinschaft (German Research Foundation). 

• Dr. Iryna Gurevych, Principal Investigator
• Prof. Dr. Max Mühlhäuser, Principal Investigator
• Dr. Jungi Kim, Project Staff