# A Purely Entity-Based Semantic Search Approach for Document Retrieval
###### Abstract  
Over the past decade, knowledge bases (KB) have been increasingly utilized to complete and enrich the representation of queries and documents in order to improve the document retrieval task. Although many approaches have used KB for such purposes, the problem of how to effectively leverage entity-based representation still needs to be resolved. This paper proposes a Purely Entity-based Semantic Search Approach for Information Retrieval (PES84 IR) as a novel solution. The approach includes (i) its own entity linking method and (ii) an inverted indexing method, and for document retrieval and ranking, (iii) an appropriate ranking method is designed to take advantage of all the strengths of the approach. We report the findings on the performance of our approach, which is tested by queries annotated by two known entity linking tools, REL and DBpedia-Spotlight. The experiments are performed on the standard TREC 2004 Robust and MSMARCO collections. By using the REL method on the Robust collection, for the queries whose terms are all annotated and whose average annotation scores are greater than or equal to 0.75, our approach achieves the maximum nDCG@5 score (1.00). Also, it is shown that using PES84 IR alongside another document retrieval method would improve performance, unless that method alone achieves the maximum nDCG@5 score for those highly annotated queries. information retrieval; document retrieval; knowledge graphs; entity-based search; entity linking +
Footnote †: journal: Applied  
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other hand, because of the complexity and dynamic nature of the queries, no document retrieval approach achieves the same performance for every query. Although a better approach has a higher performance with regard to the entire query set, a weak approach might have a better performance for some of those queries. Once these questions are effectively addressed, a document retrieval system, such as a search engine, could leverage many approaches alongside each other with regard to the different kinds of queries for better information retrieval. We propose a novel semantic search approach, named Purely Entity-based Semantic Search for Information Retrieval (PESS4 IR ([[https://github.com/EI-Emin/PESS4](https://github.com/EI-Emin/PESS4) IR-source-code]([https://github.com/EI-Emin/PESS4](https://github.com/EI-Emin/PESS4) IR-source-code))), which is based purely on entity representation, and we explore its strengths and weaknesses with regard to better document retrieval. In other words, in our approach, the \"Purely entity-based representation\" concept means that documents and queries are only represented by entities. The approach is mainly composed of three components. The first one is its own entity linking method, which is more appropriate for document text and is named Entity Linking for Document Text (EL4 DT). We note that, for the entity linking task, there are many tools available online, such as DBpedia Spotlight [11], TagMe [12], and REL [13]. However, the main reason for designing EL4 DT is that these tools do not provide certain information and statistics necessary for our document retrieval and ranking method. The second component is an inverted indexing method to achieve the indexing task. Finally, the third component is an appropriate document retrieval and ranking method, which is designed to leverage the strengths of the approach. Our approach introduces the concept of \"strong entity\" to describe entities annotated by EL4 DT with high scores (an annotation score higher than or equal to 0.85). The concept plays an important role in our retrieval and ranking method. Moreover, our approach introduces the \"related entities number\" concept to describe the number of entities semantically related to an entity, for each entity in the paragraph.