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Information Retrieval: Algorithms and Heuristics

David A. Grossman, +1 more
TLDR
This paper presents a meta-modelling architecture that automates the very labor-intensive and therefore time-heavy and expensive process of integrating structured data and text into a discrete-time system.
Abstract: 
List of Figures. Preface. 1. Introduction. 2. Retrieval Strategies. 3. Retrieval Utilities. 4. Efficiency Issues pertaining to Sequential IR Systems. 5. Integrating Structured Data and Text. 6. Parallel Information Retrieval Systems. 7. Distributed Information Retrieval. 8. The Text Retrieval Conference (TREC). 9. Future Directions. References.

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Inverted files for text search engines

Justin Zobel, +1 more
- 25 Jul 2006 - 
TL;DR: This tutorial introduces the key techniques in the area of text indexing, describing both a core implementation and how the core can be enhanced through a range of extensions.
Journal ArticleDOI

Achieving Efficient Cloud Search Services: Multi-Keyword Ranked Search over Encrypted Cloud Data Supporting Parallel Computing

Zhangjie Fu, +4 more
- 01 Jan 2015 - 
Proceedings ArticleDOI

Learning to detect malicious executables in the wild

Jeremy Z. Kolter, +1 more
TL;DR: A fielded application for detecting malicious executables in the wild is described using techniques from machine learning and data mining, and boosted decision trees outperformed other methods with an area under the roc curve of 0.996.
Journal ArticleDOI

Personalized Web search for improving retrieval effectiveness

Fang Liu, +2 more
- 01 Jan 2004 - 
TL;DR: A novel technique to learn user profiles from users' search histories is proposed, which are then used to improve retrieval effectiveness in Web search.
Proceedings ArticleDOI

Effective keyword search in relational databases

Fang Liu, +3 more
TL;DR: This paper proposes a novel IR ranking strategy for effective keyword search and is the first that conducts comprehensive experiments on search effectiveness using a real world database and a set of keyword queries collected by a major search company.