One of the distinctive features of Information Retrieval systems comparing to Database Management systems, is that they offer better compression for posting lists, resulting in better I O performance and thus faster query evaluation. In this paper, we introduce database representations of the index that reduce the size (and thus the disk I Os) of the posting lists. This is not achieved by redesigning the DBMS, but by exploiting the non 1NF features that existing Object-Relational DBM systems (ORDBMS) already offer. Specifically, four different database representations are described and detailed experimental results for one million pages are reported. Three of these representations are one order of magnitude more space efficient and faster (in query evaluation) than the plain relational representation.
In comparison to @cite_27 , this paper (a) contains a detailed discussion of all related works, (b) introduces and investigates an additional database representation (that yields smaller in size tables), (c) reports experimental results over a one order of magnitude bigger corpus, and (d) reports experimental results for document-based access tasks.
@cite_27
2156811961
Engineering a Web search engine offering effective and efficient information retrieval is a challenging task. Mitos is a recently developed search engine that offers a wide spectrum of functionalities. A rather unusual design choice is that its index is based on an object-relational database system, instead of the classical inverted file. This paper discusses the benefits and the drawbacks of this choice (compared to inverted files), proposes three different database representations, and reports comparative experimental results. Two of these representations are one order of magnitude more space economical and two orders of magnitude faster in query evaluation, than the plain relational representation.