Enriching mobile semantic search with web services

Minjae Song, Sungkwang Eom, Sangjin Shin, Kyong-Ho Lee
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Abstract

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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用web服务丰富移动语义搜索
随着移动设备数量的不断增加,大量移动数据的搜索和管理已经成为人们研究的热点。目前,大多数移动平台都为用户提供基于关键字的全文搜索(FTS),以便搜索移动数据。最近部署了语音搜索界面。然而,这些搜索方法只查询作为移动设备本地数据库输入的关键字。因此,很难弄清楚并提供用户真正想要的东西。为了克服这一限制,我们提出了一种面向移动平台的语义搜索方法。该方法根据用户的意图和上下文信息,对本地数据库的语义搜索结果进行扩充,使其具有相关的有用Web信息。虽然有各种各样的语义搜索技术,但由于移动设备数据库结构孤立、计算资源有限等特点,现有的方法很难应用于移动设备。为了在移动设备上实现语义搜索,我们还提出了一个轻量级的移动本体。提议的移动本体还与相关的Web信息保持一致,以丰富搜索结果。实验结果表明,该方法比传统的傅立叶变换方法提供了更精确的结果。此外,所提出的方法显示了可接受的响应时间和电池消耗量。
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