Entangled semantics

In the context of monolingual and bilingual retrieval, Simple Knowledge Organisation System (SKOS) datasets can play a dual role as knowledge bases for semantic annotations and as language-independent resources for translation. With no existing track of formal evaluations of these aspects for datasets in SKOS format, we describe a case study on the usage of the Thesaurus for the Social Sciences in SKOS format for a retrieval setup based on the CLEF 2004-2006 Domain-Specific Track topics, documents and relevance assessments. Results showed a mixed picture with significant system-level improvements in terms of mean average precision in the bilingual runs. Our experiments set a new and improved baseline for using SKOS-based datasets with the GIRT collection and are an example of component-based evaluation.

A model for information retrieval driven by conceptual spaces

A retrieval model describes the transformation of a query into a set of documents. The question is: what drives this transformation? For semantic information retrieval type of models this transformation is driven by the content and structure of the semantic models. In this case, Knowledge Organization Systems (KOSs) are the semantic models that encode the meaning employed for monolingual and cross-language retrieval. The focus of this research is the relationship between these meanings’ representations and their role and potential in augmenting existing retrieval models effectiveness. The proposed approach is unique in explicitly interpreting a semantic reference as a pointer to a concept in the semantic model that activates all its linked neighboring concepts. It is in fact the formalization of the information retrieval model and the integration of knowledge resources from the Linguistic Linked Open Data cloud that is distinctive from other approaches. The preprocessing of the semantic model using Formal Concept Analysis enables the extraction of conceptual spaces (formal contexts)that are based on sub-graphs from the original structure of the semantic model. The types of conceptual spaces built in this case are limited by the KOSs structural relations relevant to retrieval: exact match, broader, narrower, and related. They capture the definitional and relational aspects of the concepts in the semantic model. Also, each formal context is assigned an operational role in the flow of processes of the retrieval system enabling a clear path towards the implementations of monolingual and cross-lingual systems. By following this model’s theoretical description in constructing a retrieval system, evaluation results have shown statistically significant results in both monolingual and bilingual settings when no methods for query expansion were used. The test suite was run on the Cross-Language Evaluation Forum Domain Specific 2004-2006 collection with additional extensions to match the specifics of this model.