Using Action-Object Pairs as a Conceptual Framework for Transaction Log Analysis

Using Action-Object Pairs as a Conceptual Framework for Transaction Log Analysis

Mimi Zhang (Pennsylvania State University, USA)
Copyright: © 2009 |Pages: 20
DOI: 10.4018/978-1-59904-974-8.ch021
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Abstract

In this chapter, we present the action-object pair approach as a conceptual framework for conducting transaction log analysis. We argue that there are two basic components in the interaction between the user and the system recorded in a transaction log, which are action and object. An action is a specific expression of the user. An object is a self-contained information object, the recipient of the action. These two components form one interaction set or an action-object pair. A series of action-object pairs represents the interaction session. The action-object pair approach provides a conceptual framework for the collection, analysis, and understanding of data from transaction logs. We believe that this approach can benefit system design by providing the organizing principle for implicit feedback and other interactions concerning the user and delivering, for example, personalized service to the user based on this feedback. Action-object pairs also provide a worthwhile approach to advance our theoretical and conceptual understanding of transaction log analysis as a research method.
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Motivation

The ultimate purpose of search engine designers is to devise Web search engines that provide the most relevant information to each individual user. Since the user decides whether information is relevant or if the system is suitable, it is critical to understand the user’s system evaluation. Sun Tzu (n.d./1971), an ancient Chinese military strategist, said “know the enemy, know yourself; your victory will never be endangered” (p.129). This advice can be applied on the battlefield, but it can also apply to building information technology systems.

In a broad sense, one can understand Sun’s maxim as if you can know your own capability, and the characteristics and capabilities of people you deal with, it will be easier to devise processes appropriate to the situation. Therefore, in order to fulfill users’ information needs and serve them better, we should know the users, understand their goals, and recognize their information search tactics. If we can recognize users’ needs and their ways of approaching information, we can provide users with more suitable searching systems.

There are multiple ways to identify the individual user and provide tailored information systems. Search engines can learn about the users both explicitly and implicitly (Keenoy & Levene, 2005). In an explicit fashion, the users provide the necessary information to the system. The basis of this approach is that users would like to answer the questions, fill in a series of forms, or set up the profiles themselves. However, according to Keenoy and Levene (2005, p. 205), explicit feedback has low implementation rates due to the high cost of time and energy, unpredictable and unobvious benefits, and privacy concerns. This is in accordance with Zipf’s Law – an individual will only perform actions that cost “the least effort” (Case, 2002, p. 140). Zipf’s Law is a grounded and fundamental theoretical construct for information seeking studies. Zipf’s Law is used to guide user studies and understanding of human behaviors, as well as the development of information systems.

Rather than relying on explicit feedback by users, implicit feedback based on the analysis of interactions between the user and the system may be a better approach (Keenoy & Levene, 2005; Khopkar, Spink, Giles, Shah, & Debnath, 2003). Although it certainly depends on the design goals, the implicit approach is in many ways superior since the user does not need to perform more actions such as answering questions or setting up profiles. It is an unobtrusive method; therefore, the approach has less chance of altering users’ behavior.

The implicit approach is also highly dynamic. Since it analyzes and models current user interactions, it adapts well even if the users’ information needs change over time. White, Ruthven, and Jose (2001) compared the effectiveness of explicit and implicit feedback techniques and claimed no statistical difference between the two approaches. In addition, according to Zipf’s Law (1949), to users, the implicit feedback approach seems to be superior to the explicit feedback approach considering it costs them nothing but has the same effectiveness as the explicit feedback.

A search engine transaction log is “an electronic record of interactions that have occurred during a searching episode between a Web search engine and users searching for information on that Web search engine” (Jansen, 2006, p. 408). One can use the record of these interactions as a source of the implicit feedback. Dumais (2002) believes this is the only method for obtaining considerable amounts of data about users in a complex environment like the Web. Therefore, transaction log analysis seems a practical and convenient way to know the interactions of users with information systems. One can develop the user model by analyzing the data in transaction logs. Using this data, the system can make backward inferences to model the user and then make forward inferences to assist them with their information need.

Key Terms in this Chapter

Action: An action is a specific utterance of the user.

Object: An object is a self-contained information object, the receipt of the action.

Action-Object Pair Approach: One (a, o) pair is one interaction between the user and the system. A series of (a, o) pairs or a-o matrix can represent the interaction session, which is defined as a series of interactions between the user and the system to fulfill the user’s certain information need.

Action Object (a, o) Pair: In (a, o) pair, a stands for action and o stands for object.

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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