Semantic index for keyword search over tagged data

The index is crucial for information retrieval efficiency. Different with text data, tagged data contained rich semantics, which is useful to promote the quality of search results. It is observed that most existing indexes for keyword search do not consider semantics of tags. After an analysis of tagged data, we proposed the concept of result entity basing on the theory of relational database. We present a formula to quantify semantics of tags and then introduce a novel semantic index for keyword search. Experimental results demonstrated that our approach can help to reduce the size of the keyword inverted list in tagged document dramatically and improve the retrieval quality.

• Publication year

  2020

• Venue

  Journal of Physics: Conference Series

• Publication date

  2020-10-01

• Fields of study

  Physics, Computer Science

• Identifiers
  DOI 10.1088/1742-6596/1650/3/032041
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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