Indexes and Algorithms for Scalable and Flexible Instant Overview Search

There is an increasing interest on recommending to the user instantly (during typing characters) queries and query results. This is evidenced by the emergence of several systems that offer such functionalities (e.g. Google Instant Search, Facebook for social searching, IMDB for movie searching, etc). In this thesis we consider more informative recommendations based on various precomputed aggregated information. Such recommendations can accommodate the products of various services like autocompletion, search-as-you-type, results clustering, faceted search, entity mining, etc. The instant presentation of these recommendations helps the user (a) to discover fast what is popular among other users, (b) to decide fast which (of the suggested) query completions to use, and (c) to decide what hits of the returned answer to inspect. In this thesis we focus on making this feasible (scalable) and flexible. Regarding scalability we elaborate on an approach based on precomputed information and we comparatively evaluate various triebased index structures for making real-time interaction feasible, even if the size of the available memory space is limited. For improving the throughput that can be served we analyze and experimentally evaluate various caching policies. We report performance results over a server running on a modest personal computer (with 3 GB main memory) that provides instant services (in less than 140 ms) for millions of distinct queries and terabytes of precomputed information. As regards flexibility, in order to reduce user’s effort and to increase the exploitation of the precomputed information, we elaborate on how the recommendations can tolerate different word orders and spelling errors, assuming the proposed trie-based index structures. The experimental results revealed that such functionality significantly increases the number of recommendations especially for queries that contain several words. Euret ria kai Algìrijmoi gia Klimak ̧simh kai Euèlikth StigmiaÐa Episkopik Anaz thsh