The existing query-log based on-line index maintenance approaches rely on frequency distribution of terms in the static query-log. Though these approaches are proved to be efficient, but in real world, the frequency distribution of the terms changes over a period of time. This negatively affects the efficiency of the static query-log based approaches. To overcome this problem, we propose an index tuning strategy for reorganizing the indexes according to the latest frequency distribution of the terms captured from query-logs.Experimental results show that the proposed tuning strategy improves the performance of static query-log based approaches. © 2011 ACM.

Sreenivasa Kumar P

Department of Computer Science and Engineering

Sairam Gurajada

Frequency distributions

INDEX MAINTENANCE

INDEX TUNING

INVERTED FILES

INVERTED INDICES

QUERY LOGS

TUNING STRATEGY

Knowledge management

Maintainability

Search engines

Information retrieval

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

Index tuning for query-log based on-line index maintenance

International Conference on Information and Knowledge Management, Proceedings

In this paper, we propose a new merge-based index maintenance strategy for Information Retrieval systems. The new model is based on partitioning of the inverted index across the terms in it. We exploit the query log to partition the on-disk inverted index into two types of sub-indexes. Inverted lists of the terms contained in the queries that are frequently posed to the Information Retrieval systems are kept in one partition, called frequent-term index and the other inverted lists form another partition, called infrequent-term index. We use a lazy-merge strategy for maintaining infrequent-term sub-indexes, and an active merge strategy for maintaining frequent-term sub-indexes. The sub-indexes are also similarly split into frequent and in-frequent parts. Experimental results show that the proposed method improves both index maintenance performance and query performance compared to the existing merge-based strategies. Copyright 2009 ACM.

On-line index maintenance using horizontal partitioning

Proceedings of the sixteenth ACM conference on Conference on information and knowledge management - CIKM '07

Efficient on-line index maintenance for dynamic text collections by using dynamic balancing tree

Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '06

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Proceedings of the 1st international conference on Scalable information systems - InfoScale '06

A picture of search

Proceedings of the 14th ACM international conference on Information and knowledge management - CIKM '05

Indexing time vs. query time

Journal	International Conference on Information and Knowledge Management, Proceedings
Open Access	No