{"doi":"10.1016/j.procs.2018.01.148","title":"Enriching User Queries Using DBpedia Features and Relevance Feedback","abstract":null,"journal":"Procedia Computer Science","year":2018,"id":593289,"datarank":0.9403736931232374,"base_score":2.5649493574615367,"endowment":2.5649493574615367,"self_citation_contribution":0.38474240361923057,"citation_network_contribution":0.5556312895040069,"self_endowment_contribution":0.38474240361923057,"citer_contribution":0.5556312895040069,"corpus_percentile":null,"corpus_rank":null,"citation_count":12,"citer_count":7,"citers_with_citation_signal":6,"citers_with_endowment":6,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1518482,"name":"Abderrahim El Qadi","orcid":null,"position":1,"is_corresponding":false},{"id":1518483,"name":"Hamid Bennis","orcid":null,"position":2,"is_corresponding":false},{"id":1518481,"name":"Sarah Dahir","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Enriching User Queries Using DBpedia Features and Relevance Feedback","abstract":"Query expansion is a method for improving the effectiveness of information retrieval through the reformulation of queries by providing additional contextual information to the original queries. In this paper, we present a method to help a user redefine their queries using DBpedia's property \"dct:subject\". To achieve this purpose, we suggested an approach (SimLOD) that expands queries concepts with indexed terms, from the top 10 retrieved documents, that have similar features with the queries concepts terms' features. The proposed approach allowed us to get higher precision results than our baseline that uses queries concepts to research documents.","is_dataset_classified":null,"base_score":2.5649493574615367,"endowment":2.5649493574615367,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"26657633","pmcid":null,"openalex_id":"https://openalex.org/W2792377126","authors":[],"funders":[],"total_grants":0,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[{"year":2018,"count":1},{"year":2019,"count":2},{"year":2020,"count":2},{"year":2021,"count":4},{"year":2022,"count":3}],"oa_status":"gold","license":"cc-by-nc-nd","oa_locations":[{"url":"https://doi.org/10.1016/j.procs.2018.01.148","host_type":"journal"},{"url":"https://doi.org/10.1016/j.procs.2018.01.148","host_type":"publisher"},{"url":"https://api.elsevier.com/content/article/PII:S1877050918301601?httpAccept=text/xml","host_type":"publisher"},{"url":"https://api.elsevier.com/content/article/PII:S1877050918301601?httpAccept=text/plain","host_type":"publisher"}],"fields_of_study":["Semantic Web and Ontologies","Web Data Mining and Analysis","Advanced Database Systems and Queries"],"mesh_terms":[],"keywords":["Computer science","Information retrieval","Relevance (law)","Baseline (sea)","Subject (documents)","Property (philosophy)","Relevance feedback","World Wide Web","Artificial intelligence","Image retrieval"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Quality Education"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-26T18:46:39.533849Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}