{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T09:41:38Z","timestamp":1770889298557,"version":"3.50.1"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2016,11,5]],"date-time":"2016-11-05T00:00:00Z","timestamp":1478304000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2016,11,5]],"date-time":"2016-11-05T00:00:00Z","timestamp":1478304000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Hum. Cent. Comput. Inf. Sci."],"published-print":{"date-parts":[[2016,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>In the internet era, search engines play a vital role in information retrieval from web pages. Search engines arrange the retrieved results using various ranking algorithms. Additionally, retrieval is based on statistical searching techniques or content-based information extraction methods. It is still difficult for the user to understand the abstract details of every web page unless the user opens it separately to view the web content. This key point provided the motivation to propose and display an ontology-based object-attribute-value (O-A-V) information extraction system as a web model that acts as a user dictionary to refine the search keywords in the query for subsequent attempts. This first model is evaluated using various natural language processing (NLP) queries given as English sentences. Additionally, image search engines, such as Google Images, use content-based image information extraction and retrieval of web pages against the user query. To minimize the semantic gap between the image retrieval results and the expected user results, the domain ontology is built using image descriptions. The second proposed model initially examines natural language user queries using an NLP parser algorithm that will identify the subject-predicate-object (S-P-O) for the query. S-P-O extraction is an extended idea from the ontology-based O-A-V web model. Using this S-P-O extraction and considering the complex nature of writing SPARQL protocol and RDF query language (SPARQL) from the user point of view, the SPARQL auto query generation module is proposed, and it will auto generate the SPARQL query. Then, the query is deployed on the ontology, and images are retrieved based on the auto-generated SPARQL query. With the proposed methodology above, this paper seeks answers to following two questions. First, how to combine the use of domain ontology and semantics to improve information retrieval and user experience? Second, does this new unified framework improve the standard information retrieval systems? To answer these questions, a document retrieval system and an image retrieval system were built to test our proposed framework. The web document retrieval was tested against three key-words\/bag-of-words models and a semantic ontology model. Image retrieval was tested on IAPR TC-12 benchmark dataset. The precision, recall and accuracy results were then compared against standard information retrieval systems using TREC_EVAL. The results indicated improvements over the standard systems. A controlled experiment was performed by test subjects querying the retrieval system in the absence and presence of our proposed framework. The queries were measured using two metrics, time and click-count. Comparisons were made on the retrieval performed with and without our proposed framework. The results were encouraging.<\/jats:p>","DOI":"10.1186\/s13673-016-0074-1","type":"journal-article","created":{"date-parts":[[2016,8,4]],"date-time":"2016-08-04T11:13:33Z","timestamp":1470309213000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["A generic framework for ontology-based information retrieval and image retrieval in web data"],"prefix":"10.1186","volume":"6","author":[{"given":"V.","family":"Vijayarajan","sequence":"first","affiliation":[]},{"given":"M.","family":"Dinakaran","sequence":"additional","affiliation":[]},{"given":"Priyam","family":"Tejaswin","sequence":"additional","affiliation":[]},{"given":"Mayank","family":"Lohani","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2016,11,5]]},"reference":[{"issue":"5","key":"74_CR1","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1038\/scientificamerican0501-34","volume":"284","author":"T Berners-Lee","year":"2001","unstructured":"Berners-Lee T, Hendler J, Lassila O et al (2001) The Semantic Web. Sci Am 284(5):28\u201337","journal-title":"Sci Am"},{"key":"74_CR2","doi-asserted-by":"crossref","unstructured":"Bizer C, Heath T, Berners-Lee T (2009) Linked data-the story so far. Semantic services, interoperability and web applications: emerging concepts, p 205\u2013227","DOI":"10.4018\/978-1-60960-593-3.ch008"},{"key":"74_CR3","doi-asserted-by":"crossref","unstructured":"Meehan A, Brennan R, O\u2019Sullivan D (2015) Sparql based mapping management. In: IEEE International Conference on Semantic Computing (ICSC), 2015. IEEE, New York, p 456\u2013459","DOI":"10.1109\/ICOSC.2015.7050851"},{"issue":"1","key":"74_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2200\/S00334ED1V01Y201102WBE001","volume":"1","author":"T Heath","year":"2011","unstructured":"Heath T, Bizer C (2011) Linked data: Evolving the web into a global data space. Synth Lect Semant Web Theory Technol 1(1):1\u2013136","journal-title":"Synth Lect Semant Web Theory Technol"},{"issue":"3","key":"74_CR5","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1080\/096725500750039282","volume":"8","author":"N Kompridis","year":"2000","unstructured":"Kompridis N (2000) So we need something else for reason to mean. Int J Philos Stud 8(3):271\u2013295","journal-title":"Int J Philos Stud"},{"key":"74_CR6","doi-asserted-by":"crossref","unstructured":"Dhingra V, Bhatia KK (2015) Semcrawl: framework for crawling ontology annotated web documents for intelligent information retrieval. In: Intelligent distributed computing. Springer, Berlin, p 213\u2013223","DOI":"10.1007\/978-3-319-11227-5_19"},{"issue":"2","key":"74_CR7","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1006\/knac.1993.1008","volume":"5","author":"TR Gruber","year":"1993","unstructured":"Gruber TR (1993) A translation approach to portable ontology specifications. Knowl Acquis 5(2):199\u2013220","journal-title":"Knowl Acquis"},{"key":"74_CR8","unstructured":"Sowa JF (1999) Knowledge representation: logical, philosophical, and computational foundations"},{"key":"74_CR9","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/7287.001.0001","volume-title":"WordNet","author":"C Fellbaum","year":"1998","unstructured":"Fellbaum C (1998) WordNet. Wiley Online Library, Hoboken"},{"issue":"4","key":"74_CR10","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1093\/ijl\/3.4.235","volume":"3","author":"GA Miller","year":"1990","unstructured":"Miller GA, Beckwith R, Fellbaum C, Gross D, Miller KJ (1990) Introduction to wordnet: An on-line lexical database. Int J Lexicogr 3(4):235\u2013244","journal-title":"Int J Lexicogr"},{"key":"74_CR11","doi-asserted-by":"crossref","unstructured":"McBride B (2004) The resource description framework (rdf) and its vocabulary description language rdfs. In: Handbook on ontologies. Springer, Berlin, p 51\u201365","DOI":"10.1007\/978-3-540-24750-0_3"},{"key":"74_CR12","doi-asserted-by":"crossref","unstructured":"Mony M, Rao JM, Potey MM (2014) Semantic search based on ontology alignment for information retrieval. Int J Comput Appl 107(10)","DOI":"10.5120\/18789-0125"},{"key":"74_CR13","doi-asserted-by":"crossref","unstructured":"Enser PGB, Sandom CJ, Lewis PH (2005) Automatic annotation of images from the practitioner perspective. In: Image and video retrieval. Springer, Berlin, p 497\u2013506","DOI":"10.1007\/11526346_53"},{"issue":"5","key":"74_CR14","doi-asserted-by":"publisher","first-page":"617","DOI":"10.1016\/j.jvlc.2008.01.002","volume":"19","author":"A Hanbury","year":"2008","unstructured":"Hanbury A (2008) A survey of methods for image annotation. J Vis Lang Comput 19(5):617\u2013627","journal-title":"J Vis Lang Comput"},{"issue":"1","key":"74_CR15","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1016\/j.patcog.2006.04.045","volume":"40","author":"Y Liu","year":"2007","unstructured":"Liu Y, Zhang D, Lu G, Ma WY (2007) A survey of content-based image retrieval with high-level semantics. Pattern Recognit 40(1):262\u2013282","journal-title":"Pattern Recognit"},{"key":"74_CR16","first-page":"1","volume":"12","author":"V Vijayarajan","year":"2012","unstructured":"Vijayarajan V, Khalid M, Mouli PC (2012) A review: from keyword based image retrieval to ontology based image retrieval. Int J Rev Comput 12:1","journal-title":"Int J Rev Comput"},{"issue":"10","key":"74_CR17","first-page":"2500","volume":"8","author":"V Vijayarajan","year":"2013","unstructured":"Vijayarajan V, Dinakaran M (2013) Feature based image retrieval using fused sift and surf features. Int Rev Comput Softw 8(10):2500\u20132506","journal-title":"Int Rev Comput Softw"},{"key":"74_CR18","doi-asserted-by":"crossref","unstructured":"Shi R, Feng H, Chua TS, Lee CH (2004) An adaptive image content representation and segmentation approach to automatic image annotation. In: Image and video retrieval. Springer, Berlin, p 545\u2013554","DOI":"10.1007\/978-3-540-27814-6_64"},{"key":"74_CR19","doi-asserted-by":"crossref","unstructured":"Wang M, Zhou X, Chua TS (2008) Automatic image annotation via local multi-label classification. In: Proceedings of the 2008 international conference on content-based image and video retrieval. ACM, New York, p 17\u201326","DOI":"10.1145\/1386352.1386359"},{"issue":"4","key":"74_CR20","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1016\/j.cviu.2009.03.008","volume":"114","author":"HJ Escalante","year":"2010","unstructured":"Escalante HJ, Hern\u00e1ndez CA, Gonzalez JA, L\u00f3pez-L\u00f3pez A, Montes M, Morales EF, Sucar LE, Villase\u00f1or L, Grubinger M (2010) The segmented and annotated iapr tc-12 benchmark. Comput Vis Image Underst 114(4):419\u2013428","journal-title":"Comput Vis Image Underst"},{"key":"74_CR21","unstructured":"Grubinger M, Clough P, M\u00fcller H, Deselaers T (2006) The iapr tc-12 benchmark: a new evaluation resource for visual information systems. In: International workshop ontoImage, p 13\u201323"},{"key":"74_CR22","unstructured":"Prud E, Seaborne A, et\u00a0al (2006) Sparql query language for rdf"},{"key":"74_CR23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-68234-9_39","volume-title":"Querying distributed RDF data sources with SPARQL","author":"B Quilitz","year":"2008","unstructured":"Quilitz B, Leser U (2008) Querying distributed RDF data sources with SPARQL. Springer, Berlin"},{"key":"74_CR24","unstructured":"Jena A (2014) Fuseki: serving rdf data over http, 2014. http:\/\/jena.apache.org\/documentation\/serving_data\/. Accessed 6 Jan 2015"},{"key":"74_CR25","doi-asserted-by":"crossref","unstructured":"Pujara J, Miao H, Getoor L, Cohen W (2013) Knowledge graph identification. In: The Semantic Web\u2013ISWC 2013. Springer, Berlin, p 542\u2013557","DOI":"10.1007\/978-3-642-41335-3_34"},{"key":"74_CR26","unstructured":"Singhal A (2012) Introducing the knowledge graph: things, not strings. Official Google Blog"},{"key":"74_CR27","doi-asserted-by":"crossref","unstructured":"Wang C, Gao M, He X, Zhang R (2015) Challenges in chinese knowledge graph construction. In: 31st IEEE International conference on data engineering workshops (ICDEW), 2015. IEEE, New York, p 59\u201361","DOI":"10.1109\/ICDEW.2015.7129545"},{"key":"74_CR28","doi-asserted-by":"crossref","unstructured":"Dzbor M, Domingue J, Motta E (2003) Magpie\u2014towards a Semantic Web browser. In: The Semantic Web-ISWC 2003. Springer, Berlin, p 690\u2013705","DOI":"10.1007\/978-3-540-39718-2_44"},{"issue":"3","key":"74_CR29","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1016\/j.websem.2009.07.002","volume":"7","author":"C Bizer","year":"2009","unstructured":"Bizer C, Lehmann J, Kobilarov G, Auer S, Becker Christian, Cyganiak Richard, Hellmann Sebastian (2009) Dbpedia\u2014a crystallization point for the web of data. Web Semant Sci Serv Agents World Wide Web 7(3):154\u2013165","journal-title":"Web Semant Sci Serv Agents World Wide Web"},{"issue":"1","key":"74_CR30","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1186\/1471-2105-14-126","volume":"14","author":"J Wollbrett","year":"2013","unstructured":"Wollbrett J, Larmande P, De Lamotte F, Ruiz M (2013) Clever generation of rich sparql queries from annotated relational schema: application to Semantic Web service creation for biological databases. BMC Bioinform 14(1):126","journal-title":"BMC Bioinform"},{"key":"74_CR31","doi-asserted-by":"crossref","unstructured":"Shekarpour S (2011) Dc proposal: automatically transforming keyword queries to sparql on large-scale knowledge bases. In: The Semantic Web\u2013ISWC 2011. Springer, Berlin, p 357\u2013364","DOI":"10.1007\/978-3-642-25093-4_29"},{"key":"74_CR32","doi-asserted-by":"crossref","unstructured":"Lopez V, Pasin M, Motta E (2005) Aqualog: an ontology-portable question answering system for the Semantic Web. In: The Semantic Web: research and applications. Springer, Berlin, p 546\u2013562","DOI":"10.1007\/11431053_37"},{"issue":"6","key":"74_CR33","doi-asserted-by":"publisher","first-page":"1700","DOI":"10.1109\/TMM.2014.2326836","volume":"16","author":"Y Yang","year":"2014","unstructured":"Yang Y, Yang L, Wu G, Li S (2014) Image relevance prediction using query-context bag-of-object retrieval model. IEEE Trans Multimed 16(6):1700\u20131712","journal-title":"IEEE Trans Multimed"},{"key":"74_CR34","doi-asserted-by":"crossref","unstructured":"Vijayarajan V, Dinakaran M, Lohani M (2014) Ontology based object-attribute-value information extraction from web pages in search engine result retrieval. In: Advanced computing, networking and informatics, vol 1. Springer, Berlin, p 611\u2013620","DOI":"10.1007\/978-3-319-07353-8_70"},{"issue":"1","key":"74_CR35","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1016\/S1071-5819(02)00127-1","volume":"58","author":"JH Gennari","year":"2003","unstructured":"Gennari JH, Musen MA, Fergerson RW, Grosso WE, Crub\u00e9zy M, Eriksson H, Noy NF, Tu SW (2003) The evolution of prot\u00e9g\u00e9: an environment for knowledge-based systems development. Int J Human Comput Stud 58(1):89\u2013123","journal-title":"Int J Human Comput Stud"},{"issue":"6","key":"74_CR36","doi-asserted-by":"publisher","first-page":"853","DOI":"10.1016\/S0306-4573(02)00084-5","volume":"39","author":"P Bailey","year":"2003","unstructured":"Bailey P, Craswell N, Hawking D (2003) Engineering a multi-purpose test collection for web retrieval experiments. Inform Process Manag 39(6):853\u2013871","journal-title":"Inform Process Manag"},{"key":"74_CR37","unstructured":"Knowledge\u00a0Media Insititute (2009) Power aqua. http:\/\/technologies.kmi.open.ac.uk\/poweraqua\/trec-evaluation.html. Accessed 6 Jan 2015"},{"issue":"4","key":"74_CR38","doi-asserted-by":"publisher","first-page":"434","DOI":"10.1016\/j.websem.2010.11.003","volume":"9","author":"M Fern\u00e1ndez","year":"2011","unstructured":"Fern\u00e1ndez M, Cantador I, L\u00f3pez V, Vallet D, Castells Pablo, Motta Enrico (2011) Semantically enhanced information retrieval: an ontology-based approach. Web Semant Sci Serv Agents World Wide Web 9(4):434\u2013452","journal-title":"Web Semant Sci Serv Agents World Wide Web"},{"key":"74_CR39","unstructured":"Lucence J (2005) Jakarta lucene text search engine in java. http:\/\/jakarta.apache.org\/lucene\/docs\/index.html"}],"container-title":["Human-centric Computing and Information Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13673-016-0074-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13673-016-0074-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s13673-016-0074-1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13673-016-0074-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,7,30]],"date-time":"2021-07-30T07:53:59Z","timestamp":1627631639000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s13673-016-0074-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,11,5]]},"references-count":39,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2016,12]]}},"alternative-id":["74"],"URL":"https:\/\/doi.org\/10.1186\/s13673-016-0074-1","relation":{},"ISSN":["2192-1962"],"issn-type":[{"value":"2192-1962","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,11,5]]},"assertion":[{"value":"16 June 2015","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 July 2016","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 November 2016","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"18"}}