Social ranking for spoken web search

Spoken Web is an alternative Web for low-literacy users in the developing world. People can create audio content over phone and share on the Spoken Web. This enables easy creation of locally relevant content. Even on the World Wide Web in developed regions, the recent increase in traffic is due to the locally relevant content created on social networking sites. This paper argues that content search and ranking in the new scenario needs a re-look. The generic model of using in-links for ranking such content is not an appropriate measure of the content relevance in such a collaborative Web 2.0 world. This paper aims to bring the social context in Spoken Web ranking. We formulate a relationship function between the query-creator and the content-creator and use this as one measure of the content relevance to the user. The relationship function uses the geographical location of the two people and their prior browsing preferences as parameters to determine the relationship between the two users. Further we also determine the trustability of the content based on the content creator's acceptance measure by the social network. We use these two features in addition to the term-frequency - inverse-term-frequency match to rank the search results in context of the social network of the query-creator and provide a more specific and socially relevant result to the user.