The objective of this research is to discover the search state patterns through which users retrieve information in hypertext systems. The Markov model is used to describe users' search behavior. As determined by the log-linear model test, the second-order Markov model is the best model. Search patterns of different user groups were studied by comparing the corresponding transition probability matrices. The comparisons were made based on the following factors: gender, search experience, search task, and the user's academic background. The statistical tests revealed that there were significant differences between all the groups being compared. IntroductionThe purpose of the present study is to expand our knowledge of the actual use of hypertext systems. Specifically, I hope to discover the search state patterns through which users search for information in hypertext systems. By a search state, I mean an event in the search process, such as accessing the index or displaying an article. The questions to be investigated in this article are as follows: What is the distribution of different search states in a hypertext system? What is the probability of going from one state to another state? What states are most likely to follow one another? Do different user groups have different search state patterns? If so, how do they differ? Do differences in search tasks (general task vs. specific task) influence users' choice of states and, if so, how do they influence them? The main method for describing the search state patterns in this study is through the development of mathematical models as described below.The sequence of states that searches go through can be described mathematically by a Markov model, that is, by transition probability matrices. The Markov model is both descriptive and predictive. The datum in each cell of a transition probability matrix is the probability of going from the corresponding row state to the column state. Thus, a transition probability matrix describes a pattern of movements through states that can provide a map of the user behavior. An analysis of user behavior in this manner not only describes what proportion of a search is involved in string searching, index searching, etc., but also what states or actions are most likely to follow one another. The comparison of transition probability matrices across different user groups and search tasks will reveal the search patterns of the corresponding groups and tasks.It is necessary to define some concepts before reporting the details of this study. Hypertext is a network of nodes connected by links. A node is the basic unit used to store information, that is, a unit of text or a graph. A link is a relationship between two nodes. For example, a node that contains the citing paper and a node that contains the cited paper can be connected by the link citation. Since information is stored in nodes, users get information by visiting nodes. Because there are different types of links among nodes, there are different ways of moving from one node to the ot...
DalText, a prototype information retrieval system has been developed that permits the user to select access methods based on the task at hand. The system integrates multiple access techniques to such textual data as those generated through word processing packages, newsgroups, e-mail, etc., that are not maintained in traditional database management systems or information retrieval systems. The access methods available include viewing the data as a sequence of records for browsing, generating sets of records through string matching and Boolean combinations, and through generating a table schema and instantiating attribute values dynamically. As the access methods are all based on the same underlying data access model, the user can flip back and forth between the access methods in order to best accomplish the task at hand. An evaluation was conducted to test for correlations among a number of different variables. Of note among the results, it was found that the subjects used the access method best suited to the information task rather than relying on the access method with which they were familiar. The results indicate that further investigation should be conducted on the development of information retrieval systems that allow users to select access and display methodologies appropriate to the task at hand. IntroductionTraditionally, information systems have been developed to provide effective and efficient use of given data sets. The models used for the development of these systems have been based on characteristics of the data rather than on characteristics of the information needs of the users (Kuhlthau, 1991). For example, information retrieval (IR) Received June 1, 1993; revised November 2, 1993; accepted November 2, 1993. This research has been supported in part by the Natural Sciences and Engineering Research Council of Canada Operating Grant OGPOO09163 and by the Research and Development Fund of Dalhousie University.*To whom all correspondence should be addressed. systems (Salton, 1989) have been developed to provide users with access to relatively unstructured textual data based on the properties of word occurrences, while database management systems (DMBS) (Date, 1990) have been developed to provide users with access to more structured data, such as employee or corporate data, based on properties and values of well-defined attributes or fields within certain domains. Typically, users map their information needs into the query language of the specific system and then interpret the results within the framework of their needs. This is the data-centered paradigm for information access (Watters & Shepherd, 1992) and is based on the premises that information needs can be expressed or reformulated as distinct queries and that all needs from a data set can be satisfied by one form of output (i.e., records of text or tables of values).This approach is limited, however, as it does not take into account either the user or the task the user is attempting to perform. At the beginning of a search session, users oft...
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