The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
IEEE Intelligent Systems
Towards zero-click mobile IR evaluation: knowing what and knowing when
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
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At present, most major app marketplaces perform ranking and recommendation based on search relevance features or marketplace ``popularity'' statistics. For instance, they check similarity between app descriptions and user search queries, or rank-order the apps according to statistics such as number of downloads, user ratings etc. Rankings derived from such signals, important as they are, are insufficient to capture the dynamics of the apps ecosystem. Consider for example the questions: In a particular user context, is app A more likely to be launched than app B? Or does app C provide complementary functionality to app D-- Answering these questions requires identifying and analyzing the dependencies between apps in the apps ecosystem. Ranking mechanisms that reflect such interdependences are thus necessary. In this paper we introduce the notion of interoperability ranking for mobile applications. Intuitively, apps with high rank are such apps which are inferred to be somehow important to other apps in the ecosystem. We demonstrate how interoperability ranking can help answer the above questions and also provide the basis for solving several problems which are rapidly attracting the attention of both researchers and the industry, such as building personalized real-time app recommender systems or intelligent mobile agents. We describe a set of methods for computing interoperability ranks and analyze their performance on real data from the Windows Phone app marketplace.