# A Purely Entity-Based Semantic Search Approach for Document Retrieval
###### Abstract
Furthermore, alongside the \"strong entity\" and \"related entities number\" concepts, our retrieval and ranking method leverages many other aspects of our approach, such as document title weighting and the usage of all information and statistics stored in the index, such as the number of semantically related entities in the same paragraph (see Section 3.2). Before discussing the evaluation of our approach, it is vital to understand the nature of the purely entity-based representation of queries and documents. In fact, queries are ambiguous [6] due to the nature of their text, which is usually short and suffers from a lack of context, in contrast to document text, which could be well represented by entities because of its textual richness. Annotating the query set of the TREC 2004 Robust collection (250 queries) with the DBpedia Spotlight and REL entity linking tools highlights the \"completely annotated query\" concept; we consider a query as completely annotated when all its terms are annotated and stopwords are not obligatory. DBpedia Spotlight and REL annotate 72% and 6.8% of queries, respectively, as completely annotated queries (see Appendices A.1 and A.2). Thus, in our experiments, only completely annotated queries are considered. As our approach is designed to handle only completely annotated queries, the evaluation will be based on the corresponding results. In other words, to conduct a comparison with another method, one required the results for corresponding queries, which could be extracted from their respective result or run files. Moreover, we use the well-known baseline Galago tool [14], a search engine extended by the Lemur and Indri projects for research purposes [15], to obtain the corresponding results performed by Galago (Dirichlet method). Also, the result files of the LongP (Longformer) [16] model are used in our experiments to demonstrate the added value achieved by our approach. For our experiments, we use the TREC 2004 Robust and MSMARCO collections. We use the REL and DBpedia Spotlight entity linking tools as arbitrary entity linking methods for the query annotation process instead of our entity linking method. In other words, our approach is tested with the queries annotated by other methods. Also, in the evaluation, we use standard evaluation metrics such as normalized Discounted Cumulative Gain (nDCG@k), Mean Average Precision (MAP), and Precision (P@k). In this work, we explore the strengths and weaknesses of our approach by taking advantage of its strengths and avoiding its weaknesses. The exploration study allowed us to effectively address the main question: \"for which query a purely entity-based approach would be recommended?\". Furthermore, for queries with an average annotation score (average annotation score of query entities) higher than or equal to 0.75, as annotated by the REL method, our approach achieves the maximum nDCG@5 score (1.000), which would be an added value for any ad hoc document retrieval method which does not reach the maximum nDCG@5 score for those highly annotated queries. The remainder of the paper is organized as follows: Section 2 discusses the related work and background. Section 3 introduces the proposed approach, PES4 IR, by explaining all its components in detail. Section 4 provides the results of the performed experiments. Then, Section 5 provides the discussion of the results. Finally, the conclusion is given in Section 6.