From Analysis to Estimation of User Behavior

From Analysis to Estimation of User Behavior

Seda Ozmutlu (Uludag University, Turkey), Huseyin C. Ozmutlu (Uludag University, Turkey) and Amanda Spink (Queensland University of Technology, Australia)
Copyright: © 2009 |Pages: 21
DOI: 10.4018/978-1-59904-974-8.ch011
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Abstract

This chapter summarizes the progress of search engine user behavior analysis from search engine transaction log analysis to estimation of user behavior. Correct estimation of user information searching behavior paves the way to more successful and even personalized search engines. However, estimation of user behavior is not a simple task. It closely relates to natural language processing and human computer interaction, and requires preliminary analysis of user behavior and careful user profiling. This chapter details the studies performed on analysis and estimation of search engine user behavior, and surveys analytical methods that have been and can be used, and the challenges and research opportunities related to search engine user behavior or transaction log query analysis and estimation.
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Introduction

Search engines are the most important tools for reaching information over the Web and the effective use of search engines is a challenge (Liaw and Huang, 2006). Search engine query analysis and user behavior analysis through search engine queries is a very important task, since it is directly related to developing search engines with better performance and also personalized search engines. Analysis of user behavior is important in the sense that each service provider (and search engines are service providers) benefits from knowing its customer base and the way the customers use its services. Enhanced search engine structures and algorithms suitable for the search engine users can be developed after analyzing the behavior of the user base of the search engine.

In addition, a new trend in search engine research is the development of personalized search engines. Including personalization features into search engines has been recognized as a major research area (Liu, et al., 2004). Radlinski and Dumais (2006) state that personalizing search results for individual users is increasingly being recognized as an important future direction for searching. Agichtein, Brill, Dumai and Ragno (2006) state that accurate modeling and interpretation of user behavior have important applications to ranking, click spam detection, search personalization, and other tasks.

However, it is a real challenge to capture user information behavior, since people have different and changing information needs, and they utilize different information seeking strategies to solve their information seeking problems (Gremett, 2006). Many search studies at the human information behavior level explore the factors that influence search within the context of human information seeking (Spink and Jansen, 2004). Excellent reviews on searching exist, which we will point to within the chapter. It should also be mentioned that the chapter is restricted to studies on search engine transaction log analysis and search engine user behavior analysis and does not cover usage mining in general, which is a very wide topic.

However, it is not adequate to only analyze the user interactions with the search engine; it is also necessary to reflect the results of user query analysis to real-time information retrieval algorithms, which have estimation power of the users’ upcoming actions and transactions with the search engine. Along this direction, search engine transaction log analysis, and user behavior analysis have progressed from pure analysis of user queries to studies on estimation of content-based behavior of users, and development of personalized information retrieval algorithms.

This chapter provides the summary on the progress of search engine transaction log analysis and user behavior analysis to estimation of search engine user behavior. The chapter begins with a detailed literature review of search engine user behavior studies and continues with a detailed presentation of the methodologies used for analyzing search behavior. Then, the studies on the estimation of search use behavior will be summarized, along with the explanation of the methodologies used for these studies. The chapter is concluded with a discussion of future research opportunities.

Key Terms in this Chapter

Session Identification: Session identification is discovering the group of sequential log entries that are related to a common user or topic; new topic identification.

Analysis of Variance: Analysis of variance is a procedure, where the total variation in the dependent factor is partitioned into meaningful components (Walpole, Myers and Myers, 1998).

Monte-Carlo Simulation: Monte-Carlo simulation is a static simulation scheme that employs random numbers, and is used for solving stochastic or deterministic problems, where time plays no substantial role (Law and Kelton, 1991).

Support Vector Machines: Support vector machines is a methodology of statistical learning theory, which is based on generating functions from a set of labeled training data.

Regression: Regression is an approach that generates a model characterizing the relationship between independent and dependent factors of a system from sample data representing a certain observable fact.

Markov Models: Markov models or chains are a stochastic process that considers a finite number of values and states.

Neural Networks: A neural network is “a massively parallel distributed processor that has a natural propensity for storing experiential knowledge and making it available for use.” (Haykin, 1994).

Poisson Sampling: The Poisson sampling process is a useful random sampling process as it includes the properties of (1) Unbiased Sampling (2) Proportional Sampling (3) Comparability of Heterogeneous Poisson sampling Arrivals, and (4) Flexibility on the Stochastic Arrival Process From Which the Sample is Selected.

New Topic Identification: New topic identification is discovering when the user has switched from one topic to another during a single search session to group sequential log entries that are related to a common topic (He, Goker and Harper, 2002), session identification.

Complete Chapter List

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Table of Contents
Preface
Bernard J. Jansen, Amanda Spink, Isak Taksa
Chapter 1
Bernard J. Jansen, Isak Taksa, Amanda Spink
This chapter outlines and discusses theoretical and methodological foundations for transaction log analysis. We first address the fundamentals of... Sample PDF
Research and Methodological Foundations of Transaction Log Analysis
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Chapter 2
W. David Penniman
This historical review of the birth and evolution of transaction log analysis applied to information retrieval systems provides two perspectives.... Sample PDF
Historic Perspective of Log Analysis
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Chapter 3
Lee Rainie, Bernard J. Jansen
Every research methodology for data collection has both strengths and limitations, and this is certainly true for transaction log analysis.... Sample PDF
Surveys as a Complementary Method for Web Log Analysis
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Chapter 4
Sam Ladner
This chapter aims to improve the rigor and legitimacy of Web-traffic measurement as a social research method. I compare two dominant forms of... Sample PDF
Watching the Web: An Ontological and Epistemological Critique of Web-Traffic Measurement
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Chapter 5
Kirstie Hawkey
This chapter examines two aspects of privacy concerns that must be considered when conducting studies that include the collection of Web logging... Sample PDF
Privacy Concerns for Web Logging Data
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Chapter 6
Bernard J. Jansen
Exploiting the data stored in search logs of Web search engines, Intranets, and Websites can provide important insights into understanding the... Sample PDF
The Methodology of Search Log Analysis
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Chapter 7
Anthony Ferrini, Jakki J. Mohr
As the Web’s popularity continues to grow and as new uses of the Web are developed, the importance of measuring the performance of a given Website... Sample PDF
Uses, Limitations, and Trends in Web Analytics
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Chapter 8
Danielle Booth
This chapter is an overview of the process of Web analytics for Websites. It outlines how visitor information such as number of visitors and visit... Sample PDF
A Review of Methodologies for Analyzing Websites
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Chapter 9
Gi Woong Yun
This chapter discusses validity of units of analysis of Web log data. First, Web log units are compared to the unit of analysis of television to... Sample PDF
The Unit of Analysis and the Validity of Web Log Data
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Chapter 10
Kirstie Hawkey, Melanie Kellar
This chapter presents recommendations for reporting context in studies of Web usage including Web browsing behavior. These recommendations consist... Sample PDF
Recommendations for Reporting Web Usage Studies
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Chapter 11
Seda Ozmutlu, Huseyin C. Ozmutlu, Amanda Spink
This chapter summarizes the progress of search engine user behavior analysis from search engine transaction log analysis to estimation of user... Sample PDF
From Analysis to Estimation of User Behavior
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Chapter 12
Gheorghe Muresan
In this chapter, we describe and discuss a methodological framework that integrates analysis of interaction logs with the conceptual design of the... Sample PDF
An Integrated Approach to Interaction Design and Log Analysis
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Chapter 13
Brian Detlor, Maureen Hupfer, Umar Ruhi
This chapter provides various tips for practitioners and researchers who wish to track end-user Web information seeking behavior. These tips are... Sample PDF
Tips for Tracking Web Information Seeking Behavior
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Chapter 14
Sandro José Rigo
Adaptive Hypermedia is an effective approach to automatic personalization that overcomes the difficulties and deficiencies of traditional Web... Sample PDF
Identifying Users Stereotypes for Dynamic Web Pages Customization
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Chapter 15
Brian K. Smith, Priya Sharma, Kyu Yon Lim, Goknur Kaplan Akilli, KyoungNa Kim, Toru Fujimoto
Computers and networking technologies have led to increases in the development and sustenance of online communities, and much research has focused... Sample PDF
Finding Meaning in Online, Very-Large Scale Conversations
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Chapter 16
Isak Taksa, Sarah Zelikovitz, Amanda Spink
Search query classification is a necessary step for a number of information retrieval tasks. This chapter presents an approach to non-hierarchical... Sample PDF
Machine Learning Approach to Search Query Classification
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Chapter 17
Seda Ozmutlu, Huseyin C. Ozmutlu, Amanda Spink
This chapter emphasizes topic analysis and identification of search engine user queries. Topic analysis and identification of queries is an... Sample PDF
Topic Analysis and Identification of Queries
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Chapter 18
Elmer V. Bernstam, Jorge R. Herskovic, William R. Hersh
Clinicians, researchers and members of the general public are increasingly using information technology to cope with the explosion in biomedical... Sample PDF
Query Log Analysis in Biomedicine
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Chapter 19
Michael Chau, Yan Lu, Xiao Fang, Christopher C. Yang
More non-English contents are now available on the World Wide Web and the number of non-English users on the Web is increasing. While it is... Sample PDF
Processing and Analysis of Search Query Logs in Chinese
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Chapter 20
Udo Kruschwitz, Nick Webb, Richard Sutcliffe
The theme of this chapter is the improvement of Information Retrieval and Question Answering systems by the analysis of query logs. Two case studies... Sample PDF
Query Log Analysis for Adaptive Dialogue-Driven Search
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Chapter 21
Mimi Zhang
In this chapter, we present the action-object pair approach as a conceptual framework for conducting transaction log analysis. We argue that there... Sample PDF
Using Action-Object Pairs as a Conceptual Framework for Transaction Log Analysis
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Chapter 22
Paul DiPerna
This chapter proposes a new theoretical construct for evaluating Websites that facilitate online social networks. The suggested model considers... Sample PDF
Analysis and Evaluation of the Connector Website
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Chapter 23
Marie-Francine Moens
This chapter introduces information extraction from blog texts. It argues that the classical techniques for information extraction that are commonly... Sample PDF
Information Extraction from Blogs
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Chapter 24
Adriana Andrade Braga
This chapter explores the possibilities and limitations of nethnography, an ethnographic approach applied to the study of online interactions... Sample PDF
Nethnography: A Naturalistic Approach Towards Online Interaction
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Chapter 25
Isak Taksa, Amanda Spink, Bernard J. Jansen
Web log analysis is an innovative and unique field constantly formed and changed by the convergence of various emerging Web technologies. Due to its... Sample PDF
Web Log Analysis: Diversity of Research Methodologies
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