Semantic technologies such as controlled vocabularies, thesauri, and knowledge graphs have been used throughout the history of information retrieval for a variety of tasks. Recent advances in knowledge acquisition, alignment, and utilization have given rise to a body of new approaches for utilizing knowledge graphs in text retrieval tasks. This workshop focuses on the end-to-end utilization of knowledge graphs and semantics in text retrieval, text understanding and other IR-related applications. Its scope covers the acquisition, the alignment, and the utilization of knowledge graphs and semantic resources for the purpose of optimizing end-to-end performance of a system that responds to a user's information need. Examples of such technologies and applications include entity ranking, entity linking, entity-based retrieval models, entity recommendation, document filtering, knowledge graph population, and more. The goal of the KG4IR workshop is to consolidate the community eforts and study how such technologies can be employed in information retrieval systems in the most efective way. We are calling for papers on ongoing research and position papers as well as talk abstracts for future trends, tasks, and open problems to ensure that breakthroughs, and, technologies algorithms in this space are widely disseminated. We are particularly interested in practical experiences with KG technology both from academia and industry.
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In: Joint Proceedings of the First International Workshop on Professional Search (ProfS2018); the Second Workshop on Knowledge Graphs and Semantics for Text Retrieval, Analysis, and Understanding (KG4IR); and the International Workshop on Data Search (DATA:SEARCH’18). Co-located with SIGIR 2018, Ann Arbor, Michigan, USA – 12 July 2018, published at http://ceur-ws.org
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