Exploiting Semantic Annotations for Domain-Specific Entity Search

  • Tuukka Ruotsalo
  • Eero Hyvönen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9022)


Searches on the Web of Data go beyond the retrieval of textual Web sites, and shifts the focus of search engines towards domain-specific entity data, for which the units of retrieval are domain-specific entities instead of textual documents. We study the effect of using semantic annotation in combination with a knowledge graph for domain-specific entity search. Different reasoning, indexing and query-expansion strategies are compared to study their effect in improving the effectiveness of entity search. The results show that the use of semantic annotation and background knowledge can significantly improve the retrieval effectiveness, but require graph structures to be exploited beyond standard reasoning. Our findings can help to develop more effective information and data retrieval methods that can enhance the performance of semantic search engines that operate with structured domain-specific Web data.


Query Expansion Semantic Annotation Semantic Search Knowledge Graph Random Walk Approach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Tuukka Ruotsalo
    • 1
  • Eero Hyvönen
    • 2
  1. 1.Helsinki Institute for Information Technology HIITAalto UniversityFinland
  2. 2.Semantic Computing Research Group (SeCo)Aalto UniversityFinland

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