Keyword Based Semantic Search for Mobile Data

Ko, Jihoon; Shin, Sangjin; Eom, Sungkwang; Song, Minjae; Jung, Jason J.; Shin, Dong Hoon; Lee, Kyong-Ho; Jang, Yongil

doi:10.1109/mdm.2014.36

Cited by 3 publications

(1 citation statement)

References 7 publications

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“…FTS may not reflect a user’s query intention, namely exactly what a user wants; it just returns search results that include given keywords as substrings. This is caused by a limitation with the current mobile platforms that do not support a sophisticated search based on semantic relationships among mobile data, which are stored over multiple databases (DBs) [2]. In detail, mobile platforms store each application data in its dedicated DB, which is isolated from the others for security reasons.…”

Section: Introductionmentioning

confidence: 99%

Keyword-based mobile semantic search using mobile ontology

Shin

Eom

et al. 2014

Journal of Information Science

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A large volume of mobile data is being generated and shared among mobile devices such as smartphones. Most of the mobile platforms provide a user with a keyword-based full text search (FTS) in order to search for mobile data. However, FTS only returns the data corresponding to the keywords given by users as results without considering a user’s query intention. To overcome this limitation, we propose a semantically enhanced keyword-based search method. Although there are various semantic search techniques, it is hard to apply existing methods to mobile devices just as they are. This is caused by the characteristics of mobile devices such as isolated database structures and limited computing resources. To enable semantic search on mobile devices, we also propose a lightweight mobile ontology. Experimental results from the prototype implementation of the proposed method show that the proposed method provides a better user experience than the conventional FTS and returns accurate search results in an acceptable response time.

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Section: Introductionmentioning

confidence: 99%

Keyword-based mobile semantic search using mobile ontology

Shin

Eom

et al. 2014

Journal of Information Science

Self Cite

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Split keyword fuzzy and synonym search over encrypted cloud data

Raghavendra

Girish

Geeta

et al. 2017

Multimed Tools Appl

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Enriching mobile semantic search with web services

Song

Eom

Shin

et al. 2015

Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015)

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With the increasing number of mobile devices, there have been many researches on searching and managing a large volume of mobile data. Most of the mobile platforms today provide users with keyword-based full text search (FTS) in order to search for mobile data. Recently, voice search interfaces have been deployed. These search methods, however, query only the keywords given as an input to local databases in mobile devices. Therefore, it is quite difficult to figure out and to provide what a user really wants. To overcome this limitation, we propose a semantic search method for mobile platforms. The proposed method augments the results of semantic search on local databases with their related useful Web information according to the intention and context information of a user. Although there are various semantic search techniques, it is hard to apply the existing methods to mobile devices due to the characteristics of mobile devices such as isolated database structures and limited computing resources. To enable semantic search on mobile devices, we also propose a lightweight mobile ontology. The proposed mobile ontology is also aligned with related Web information to enrich search results. Experimental results from prototype implementation of the proposed method verify that our approach provides more accurate results than the conventional FTS does. In addition, the proposed method shows an acceptable amount of response time and battery consumption.

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Keyword Based Semantic Search for Mobile Data

Cited by 3 publications

References 7 publications

Keyword-based mobile semantic search using mobile ontology

Keyword-based mobile semantic search using mobile ontology

Split keyword fuzzy and synonym search over encrypted cloud data

Enriching mobile semantic search with web services

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