Information retrieval in mobile phones using snippet clustering methods

In recent years there has been tremendous growth in the computational capabilities of devices, content and the retrieval methods. There is great interest now in the mobile web. Mobile web refers to access to the web via a browser or application from a mobile computing system. The mobile computing system can be a mobile computer, smart phone or even a mobile phone. The access to the web from a mobile device especially the search for information is growing in popularity every day due to the availability, cheap cost and convenience of access. Studies have shown that the users are not satisfied with the state of the art in mobile browsing especially in the search and retrieval process. The potentially large volume of content that can be accessed, low power limitations of cellular band width, variable and small screen sizes pose considerable challenges to mobile users. This has necessitated great interest and research in the domain. This paper proposes a middleware based system that retrieves content dynamically from the web based on the user context, personal preferences and uses adapted snippet clustering algorithms for re ranking the query results. The architecture of the mobile information retrieval system is given along with the discussion on the prototypes used to validate the results. The initial results are promising and show considerable potential for research in the domain.