User-Centered Indexing for Adaptive Information Access
01 Jan 1996-User Modeling and User-adapted Interaction (Springer, Dordrecht)-Vol. 6, Iss: 2, pp 171-207
TL;DR: This work proposes a solution which provides user-centered adaptive information retrieval and navigation which is complementary to information discovery methods which provide access to new information, and automatically manages its size in order to maintain rapid access when scaling up to large hypermedia space.
Abstract: We are focusing on information access tasks characterized by large volume of hypermedia connected technical documents, a need for rapid and effective access to familiar information, and long-term interaction with evolving information. The problem for technical users is to build and maintain a personalized task-oriented model of the information to quickly access relevant information. We propose a solution which provides user-centered adaptive information retrieval and navigation. This solution supports users in customizing information access over time. It is complementary to information discovery methods which provide access to new information, since it lets users customize future access to previously found information. It relies on a technique, called Adaptive Relevance Network, which creates and maintains a complex indexing structure to represent personal user’s information access maps organized by concepts. This technique is integrated within the Adaptive HyperMan system, which helps NASA Space Shuttle flight controllers organize and access large amount of information. It allows users to select and mark any part of a document as interesting, and to index that part with user-defined concepts. Users can then do subsequent retrieval of marked portions of documents. This functionality allows users to define and access personal collections of information, which are dynamically computed. The system also supports collaborative review by letting users share group access maps. The adaptive relevance network provides long-term adaptation based both on usage and on explicit user input. The indexing structure is dynamic and evolves over time. Learning and generalization support flexible retrieval of information under similar concepts. The network is geared towards more recent information access, and automatically manages its size in order to maintain rapid access when scaling up to large hypermedia space. We present results of simulated learning experiments.
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TL;DR: This paper is a review of existing work on adaptive hypermedia and introduces several dimensions of classification of AH systems, methods and techniques and describes the most important of them.
Abstract: Adaptive hypermedia is a new direction of research within the area of adaptive and user model-based interfaces. Adaptive hypermedia (AH) systems build a model of the individual user and apply it for adaptation to that user, for example, to adapt the content of a hypermedia page to the user's knowledge and goals, or to suggest the most relevant links to follow. AH systems are used now in several application areas where the hyperspace is reasonably large and where a hypermedia application is expected to be used by individuals with different goals, knowledge and backgrounds. This paper is a review of existing work on adaptive hypermedia. The paper is centered around a set of identified methods and techniques of AH. It introduces several dimensions of classification of AH systems, methods and techniques and describes the most important of them.
1,948 citations
01 Jan 2007
TL;DR: This chapter complements other chapters of this book in reviewing user models and user modeling approaches applied in adaptive Web systems by focusing on the overlay approach to user model representation and the uncertainty-based approach touser modeling.
Abstract: One distinctive feature of any adaptive system is the user model that represents essential information about each user This chapter complements other chapters of this book in reviewing user models and user modeling approaches applied in adaptive Web systems The presentation is structured along three dimensions: what is being modeled, how it is modeled, and how the models are maintained After a broad overview of the nature of the information presented in these various user models, the chapter focuses on two groups of approaches to user model representation and maintenance: the overlay approach to user model representation and the uncertainty-based approach to user modeling
869 citations
TL;DR: Rules of thumb for experimental design, useful tests for covariates, and common threats to experimental validity are presented and Reporting standards including effect size and power are proposed.
Abstract: Empirical evaluations are needed to determine which users are helped or hindered by user-adapted interaction in user modeling systems. A review of past UMUAI articles reveals insufficient empirical evaluations, but an encouraging upward trend. Rules of thumb for experimental design, useful tests for covariates, and common threats to experimental validity are presented. Reporting standards including effect size and power are proposed.
268 citations
01 Feb 1998
TL;DR: This paper presents a meta-modelling approach to user modeling in the Interactive Anatomy Tutoring System ANATOM-TUTOR and discusses Hypadapter, an Adaptive Hypertext System for Exploratory Learning and Programming.
Abstract: Preface. 1. Methods and Techniques of Adaptive Hypermedia P. Brusilovsky. 2. Adaptive Hypertext Navigation Based on User Goals and Context C. Kaplan, et al. 3. Metadoc: An Adaptive Hypertext Reading System C. Boyle, A.O. Encarnacion. 4. User Modelling in the Interactive Anatomy Tutoring System ANATOM-TUTOR I.H. Beaumont. 5. Hypadapter: An Adaptive Hypertext System for Exploratory Learning and Programming H. Hohl, et al. 6. A Glass Box Approach to Adaptive Hypermedia K. Hook, et al. 7. User-Centered Indexing for Adaptive Information Access N. Mathe, J.R. Chen. 8. A Task-Centred Approach for User Modeling a Hypermedia Office Documentation System J. Vassileva. Index.
247 citations
TL;DR: Although social network metrics and ISI IF rankings deviate moderately for citation-based journal networks, they differ considerably for journal networks derived from download data, which raises questions regarding the validity of the ISI IF as the sole assessment of journal impact.
Abstract: We generated networks of journal relationships from citation and download data, and determined journal impact rankings from these networks using a set of social network centrality metrics. The resulting journal impact rankings were compared to the ISI IF. Results indicate that, although social network metrics and ISI IF rankings deviate moderately for citation-based journal networks, they differ considerably for journal networks derived from download data. We believe the results represent a unique aspect of general journal impact that is not captured by the ISI IF. These results furthermore raise questions regarding the validity of the ISI IF as the sole assessment of journal impact, and suggest the possibility of devising impact metrics based on usage information in general.
211 citations
References
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TL;DR: An approach based on space density computations is used to choose an optimum indexing vocabulary for a collection of documents, demonstating the usefulness of the model.
Abstract: In a document retrieval, or other pattern matching environment where stored entities (documents) are compared with each other or with incoming patterns (search requests), it appears that the best indexing (property) space is one where each entity lies as far away from the others as possible; in these circumstances the value of an indexing system may be expressible as a function of the density of the object space; in particular, retrieval performance may correlate inversely with space density. An approach based on space density computations is used to choose an optimum indexing vocabulary for a collection of documents. Typical evaluation results are shown, demonstating the usefulness of the model.
6,619 citations
PARC1
TL;DR: Tapestry is intended to handle any incoming stream of electronic documents and serves both as a mail filter and repository; its components are the indexer, document store, annotation store, filterer, little box, remailer, appraiser and reader/browser.
Abstract: The Tapestry experimental mail system developed at the Xerox Palo Alto Research Center is predicated on the belief that information filtering can be more effective when humans are involved in the filtering process. Tapestry was designed to support both content-based filtering and collaborative filtering, which entails people collaborating to help each other perform filtering by recording their reactions to documents they read. The reactions are called annotations; they can be accessed by other people’s filters. Tapestry is intended to handle any incoming stream of electronic documents and serves both as a mail filter and repository; its components are the indexer, document store, annotation store, filterer, little box, remailer, appraiser and reader/browser. Tapestry’s client/server architecture, its various components, and the Tapestry query language are described.
4,299 citations
Book•
03 Jan 1989
3,571 citations
[...]
TL;DR: In this approach to software development, application programs are written as software agents, i.e. software “components” that communicate with their peers by exchanging messages in an expressive agent communication language.
Abstract: The software world is one of great richness and diversity. Many thousands of software products are available to users today, providing a wide variety of information and services in a wide variety of domains. While most of these programs provide their users with significant value when used in isolation, there is increasing demand for programs that can interoperate – to exchange information and services with other programs and thereby solve problems that cannot be solved alone. Part of what makes interoperation difficult is heterogeneity. Programs are written by different people, at different times, in different languages; and, as a result, they often provide different interfaces. The difficulties created by heterogeneity are exacerbated by dynamics in the software environment. Programs are frequently rewritten; new programs are added; old programs removed. Agent-based software engineering was invented to facilitate the creation of software able to interoperate in such settings. In this approach to software development, application programs are written as software agents, i.e. software “components” that communicate with their peers by exchanging messages in an expressive agent communication language. Agents can be as simple as subroutines; but typically they are larger entities with some sort of persistent control (e.g. distinct control threads within a single address space, distinct processes on a single machine, or separate processes on different machines). The salient feature of the language used by agents is its expressiveness. It allows for the exchange of data and logical information, individual commands and scripts (i.e. programs). Using this language, agents can communicate complex information and goals, directly or indirectly “programming” each other in useful ways. Agent-based software engineering is often compared to object-oriented programming. Like an “object”, an agent provides a message-based interface independent of its internal data structures and algorithms. The primary difference between the two approaches lies in the language of the interface. In general object-oriented programming, the meaning of a message can vary from one object to another. In agent-based software engineering, agents use a common language with an agent-independent semantics. The concept of agent-based software engineering raises a number of important questions.
2,373 citations
Book•
01 Dec 1988
TL;DR: This paper examines statistical techniques for exploiting relevance information to weight search terms using information about the distribution of index terms in documents in general and shows that specific weighted search methods are implied by a general probabilistic theory of retrieval.
Abstract: This paper examines statistical techniques for exploiting relevance information to weight search terms. These techniques are presented as a natural extension of weighting methods using information about the distribution of index terms in documents in general. A series of relevance weighting functions is derived and is justified by theoretical considerations. In particular, it is shown that specific weighted search methods are implied by a general probabilistic theory of retrieval. Different applications of relevance weighting are illustrated by experimental results for test collections.
2,105 citations