Adaptive hypermedia is a relatively new direction of research on the crossroads of hypermedia and user modeling. Adaptive hypermedia systems build a model of the goals, preferences and knowledge of each individual user, and use this model throughout the interaction with the user, in order to adapt to the needs of that user. The goal of this paper is to present the state of the art in adaptive hypermedia at the eve of the year 2000, and to highlight some prospects for the future. This paper attempts to serve both the newcomers and the experts in the area of adaptive hypermedia by building on an earlier comprehensive review (Brusilovsky, 1996; Brusilovsky, 1998).

Adaptive Hypermedia

In this article, we performed a comparative study to investigate the performance of methods for detecting emerging research fronts. Three types of citation network, co-citation, bibliographic coupling, and direct citation, were tested in three research domains, gallium nitride (GaN), complex network (CNW), and carbon nanotube (CNT). Three types of citation network were constructed for each research domain, and the papers in those domains were divided into clusters to detect the research front. We evaluated the performance of each type of citation network in detecting a research front by using the following measures of papers in the cluster: visibility, measured by normalized cluster size, speed, measured by average publication year, and topological relevance, measured by density. Direct citation, which could detect large and young emerging clusters earlier, shows the best performance in detecting a research front, and co-citation shows the worst. Additionally, in direct citation networks, the clustering coefficient was the largest, which suggests that the content similarity of papers connected by direct citations is the greatest and that direct citation networks have the least risk of missing emerging research domains because core papers are included in the largest component. © 2009 Wiley Periodicals, Inc.

Comparative study on methods of detecting research fronts using different types of citation

An adaptive interface for a programmable system, for predicting a desired user function, based on user history, as well as machine internal status and context. The apparatus receives an input from the user and other data. A predicted input is presented for confirmation by the user, and the predictive mechanism is updated based on this feedback. Also provided is a pattern recognition system for a multimedia device, wherein a user input is matched to a video stream on a conceptual basis, allowing inexact programming of a multimedia device. The system analyzes a data stream for correspondence with a data pattern for processing and storage. The data stream is subjected to adaptive pattern recognition to extract features of interest to provide a highly compressed representation that may be efficiently processed to determine correspondence. Applications of the interface and system include a video cassette recorder (VCR), medical device, vehicle control system, audio device, environmental control system, securities trading terminal, and smart house. The system optionally includes an actuator for effecting the environment of operation, allowing closed-loop feedback operation and automated learning.

Adaptive pattern recognition based control system and method

An information retrieval system allows a user to navigate through a plurality of informational items for a desired informational items, and upon selection of an information item, presents other informational items related to the selected informational item. The information retrieval system in accordance with the principles of the present invention maintains a database that defines a relational association between a plurality of informational items in the system. The relational association is based on historical navigational behavior of users of the information retrieval system, and includes a relationship type, which is based on the characteristic similarities between the informational items, and relationship strength, which is based on the historical frequency of any related informational items being selected by a user within the same information retrieval session. When a navigation from one informational item to another information item is detected, the relationship type and the relationship strength of the two informational items are determined and stored in the database. During a subsequent selection of an informational item, any related informational items related to the selected informational item are sorted based on the respective relationship types and relationship strengths, and are provided in a sorted list from which the user can select.

Usage based strength between related information in an information retrieval system

With the growth of the Web, there has been a rapid increase in the number of users who need to access online databases without having a detailed knowledge of the schema or of query languages; even relatively simple query languages designed for non-experts are too complicated for them. We describe BANKS, a system which enables keyword-based search on relational databases, together with data and schema browsing. BANKS enables users to extract information in a simple manner without any knowledge of the schema or any need for writing complex queries. A user can get information by typing a few keywords, following hyperlinks, and interacting with controls on the displayed results. BANKS models tuples as nodes in a graph, connected by links induced by foreign key and other relationships. Answers to a query are modeled as rooted trees connecting tuples that match individual keywords in the query. Answers are ranked using a notion of proximity coupled with a notion of prestige of nodes based on inlinks, similar to techniques developed for Web search. We present an efficient heuristic algorithm for finding and ranking query results.

/pdf/keyword-searching-and-browsing-in-databases-using-banks-3ktuauorb3.pdf

Keyword searching and browsing in databases using BANKS

The present invention provides a hypermedia database for managing bookmarks, which allows a user to organize hypertext documents for querying, navigating, sharing and viewing. In addition, the hypermedia database also provides access control to the information in the database. The hypermedia database of the present invention parses meta-data from bookmarked documents and indexes and classifies the documents. The present invention supports advanced query and navigation of a collection of bookmarks, especially providing various personalized bookmark services. In one embodiment, the present invention utilizes a proxy server to observe a user's access patterns to provide useful personalized services, such as automated URL bookmarking, document refresh, and bookmark expiration. In addition, a user may also specify various preference in bookmark management, e.g., ranking schemes (i.e. by referral, access frequency, or popularity) and navigation tree fan-out. A subscription service which retrieves new or updated documents of user-specified interests is also provided.

System for personalizing, organizing and managing web information

Since WWW encourages hypertext and hypermedia document authoring (e.g., HTML or XML), Web authors tend to create documents that are composed of multiple pages connected with hyperlinks or frames. A Web document may be authored in multiple ways, such as (1) all information in one physical page, or (2) a main page and the related information in separate linked pages. Existing Web search engines, however, return only physical pages. In this paper, we introduce and describe the use of the concept of information unit, which can be viewed as a logical Web document consisting of multiple physical pages as one atomic retrieval unit. We present an algorithm to eAEciently retrieve information units. Our algorithm can perform progressive query processing over a Web index by considering both document semantic similarity and link structures. Experimental results on synthetic graphs and real Web data show the effectiveness and usefulness of the proposed information unit retrieval technique.

https://www.public.asu.edu/~candan/papers/w10_iu.pdf

Retrieving and organizing web pages by “information unit”

Users of the Web are overloaded with information. This medium is “polluted” with redundant, erroneous and low quality information. A WWW survey of 11,700 users conducted from April 10 to May 10, 1996[1] indicates that 30.31% of the users report “finding known info” is their problem and 27.80% of the users report organizing collected information as their problem. An empirical study[2] on users’ revisitation patterns to WWW pages found that 58% of an individual’s pages are revisits. With these study results, we believe the Web users would like to build and organize a larger collection of bookmarks for future references than they can reasonably maintain now.

PowerBookmarks: a system for personalizable Web information organization, sharing, and management

We extend the notion of bookmark management by introducing the functionalities of hypermedia databases. PowerBookmarks is a Web information organization, sharing, and management tool, which parses metadata from bookmarked URLs and uses it to index and classify the URLs. PowerBookmarks supports advanced query, classification, and navigation functionalities on collections of bookmarks. PowerBookmarks monitors and utilizes users' access patterns to provide many useful personalized services, such as automated URL bookmarking, document refreshing, and bookmark expiration. It also allows users to specify their preference in bookmark management, such as ranking schemes and classification tree structures. Subscription services for new or updated documents of users' interests are also supported.

A method for constructing and maintaining a navigation tree based on external document classifiers is provided. In one embodiment, based on the returned category labels from the classifiers, a navigation tree is constructed by taking usability and user preferences into consideration. Control parameters and algorithms are provided for inserting into and deleting documents from the navigation tree, and for splitting and merging nodes of the navigation tree, are provided.

Personalized navigation trees

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System for personalizing, organizing and managing web information

Retrieving and organizing web pages by “information unit”

PowerBookmarks: a system for personalizable Web information organization, sharing, and management

PowerBookmarks: a system for personalizable Web information organization, sharing, and management

Personalized navigation trees