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Inverted File-Based General Metric Space Indexing for Quality-Aware Similarity Search in Information Retrieval

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Quality Issues in the Management of Web Information

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 50))

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Abstract

The notion of quality in its broadest sense is central to information retrieval (IR) where a user’s information need is to be fulfilled as good as possible. A user searching for cars on sale in Bamberg might be interested in car dealers geographically close to Bamberg with high user ratings. The buyer might already know or trust a person who trusts the particular dealer. Furthermore, the cars which are sold by the dealer should offer a high quality on different levels–the type of car in general as well as the car to be bought. If the buyer can only travel to Bamberg on weekends, availability of the car dealer becomes another important factor. As this example shows, the integration of various quality aspects in IR is challenging but essential.

Thus, there is a need for scalable and efficient indexing and retrieval techniques which can cope with such search situations. Here, metric space access methods (MAMs) present a flexible indexing paradigm.We will briefly review these techniques and show how they can be applied in the context of qualityaware IR. Furthermore, we will present IF4MI which is purely based on the inverted file concept and thus inherently provides a multi-feature MAM. It can make use of extensive knowledge in the field of inverted file-based indexing and represents a versatile indexing technique for quality-aware IR.

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Authors and Affiliations

  1. Media Informatics Group, University of Bamberg, 96052, Bamberg, Germany

    Daniel Blank & Andreas Henrich

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  1. Daniel Blank
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  2. Andreas Henrich
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Correspondence to Daniel Blank .

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  1. Milano Bicocca, Dipartimento di Informatica, Universita' degli Studi di, Edificio U14, Viale Sarca 336, Milano, 20126, Italy

    Gabriella Pasi

  2. CNR IDPA Inst. f. Environmental, Process Dynamics, Italian National Research Council, Via Pasubio 5, Dalmine, 24044, Italy

    Gloria Bordogna

  3. , School of Electrical and Information, University of South Australia, Adelaide, 5095, South Australia, Australia

    Lakhmi C. Jain

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Blank, D., Henrich, A. (2013). Inverted File-Based General Metric Space Indexing for Quality-Aware Similarity Search in Information Retrieval. In: Pasi, G., Bordogna, G., Jain, L. (eds) Quality Issues in the Management of Web Information. Intelligent Systems Reference Library, vol 50. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37688-7_2

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  • DOI: https://doi.org/10.1007/978-3-642-37688-7_2

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