Hybrid query processing for personalized information retrieval on the Semantic Web

Yoo, Dong-Keun

doi:10.1016/j.knosys.2011.10.004

Cited by 27 publications

(11 citation statements)

References 19 publications

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“…Additionally, an user study reveals the acceptance of the Hybrid Search paradigm by end users. A personalized hybrid search implementing a hotel search service as use case is presented in [23]. By combining rule-based personal knowledge inference over subjective data, such as expensive locations, and reasoning, the personalized hybrid search has been proven to return a smaller amount of data thus resulting in more precise answers.…”

Section: Hybrid Searchmentioning

confidence: 99%

HAWK – Hybrid Question Answering Using Linked Data

Usbeck

Ngomo

Bühmann

et al. 2015

Lecture Notes in Computer Science

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Abstract. The decentral architecture behind the Web has led to pieces of information being distributed across data sources with varying structure. Hence, answering complex questions often required combining information from structured and unstructured data sources. We present HAWK, a novel entity search approach for Hybrid Question Answering based on combining Linked Data and textual data. The approach uses predicate-argument representations of questions to derive equivalent combinations of SPARQL query fragments and text queries. These are executed so as to integrate the results of the text queries into SPARQL and thus generate a formal interpretation of the query. We present a thorough evaluation of the framework, including an analysis of the influence of entity annotation tools on the generation process of the hybrid queries and a study of the overall accuracy of the system. Our results show that HAWK achieves 0.68 respectively 0.61 F-measure within the training respectively test phases on the Question Answering over Linked Data (QALD-4) hybrid query benchmark.

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Section: Hybrid Searchmentioning

confidence: 99%

HAWK – Hybrid Question Answering Using Linked Data

Usbeck

Ngomo

Bühmann

et al. 2015

Lecture Notes in Computer Science

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“…With the intelligent ATCIS, we have developed a commanders' decision support service based on the query rewriting method [15] to resolve the problem. Here, we describe the core function of the service, which is conducted via rewritten SPARQL queries instead of the reasoning engine to create relevant military knowledge in a short time.…”

Section: Commanders' Decision Support Servicementioning

confidence: 99%

A Practical Military Ontology Construction for the Intelligent Army Tactical Command Information System

Yoo

2014

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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The purpose of this research is to construct a military ontology as the core element for implementing the intelligent Army Tactical Command Information System (ATCIS). Using the military ontology, the system can automatically understand and manage the meaning of military information in the system, and hence it can provide a commander with military knowledge for decision making. To construct the military ontology, we define the core concepts of the ontology based on terms extracted from the ATCIS database and complete the ontology by using the mixed ontology building methodology (MOBM). In addition, we implement intelligent ATCIS as a prototype that provides a military concept navigation service and commanders' decision support service to demonstrate how to use the military ontology in practice.

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“…This method has overcome very frequent accessibility for short periods of time using advance data structures technique. Yoo [14] supports effective retrieval of personalized information on the semantic web by using hybrid query processing method. The hybrid of two methods, query rewriting method and reasoning method are able to process query when individual requirements change.…”

Section: User Profiling/personalizationmentioning

confidence: 99%

“…While ontologies are capable in giving good outcome, researchers are trying to enhance searching method using clustering technique [11] and user profiling/personalization [12,13,14]. Although previous researches are capable to give good results, we are motivated to improve the output.…”

Section: Introductionmentioning

confidence: 99%

Semantic Web Search Engine Using Ontology, Clustering and Personalization Techniques

Abdullah

Ibrahim

2012

Computational Science and Its Applications – ICCSA 2012

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Abstract. Data accuracy and reliability have been a serious issue in the vast emergence of information on the web. Advanced web searching has assisted in knowledge retrieving. However, most knowledge on the Web is presented in natural-language text that understandable by human but difficult for computers to interpret. Therefore, Semantic Web approach is widely used to give more reliable application. This paper presents a framework in enhancing knowledge retrieval processes using Semantic Web technologies. Instead of using ontology and categorization alone, we are injecting personalization concept from Relational Database (RDB) to ensure more reliable data are obtained. The proposed framework is discussed in details. A case study is presented to see the viability of the proposed framework in retrieving the meaningful information.

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Hybrid query processing for personalized information retrieval on the Semantic Web

Cited by 27 publications

References 19 publications

HAWK – Hybrid Question Answering Using Linked Data

HAWK – Hybrid Question Answering Using Linked Data

A Practical Military Ontology Construction for the Intelligent Army Tactical Command Information System

Semantic Web Search Engine Using Ontology, Clustering and Personalization Techniques

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