Tailoring Automatically Generated Hypertext

This paper describes an approach for tailoring the content and structure of automatically generated hypertext. The implemented system HYLITE is based on applied Natural Language Generation (NLG) techniques, a re-usable user modelling component (VIEWGEN), and a flexible architecture with module feedback. The user modelling component is used by the language generation modules to adapt the hypertext content and links to user beliefs and preferences and to the previous interaction. Unlike previous adaptive NLG systems, which have their own, application-specific user models, HYLITE has re-used a generic agent modelling framework (VIEWGEN) instead. Apart from avoiding the development costs of a new model, this also enabled a more extendable system architecture. Another distinct feature of our approach is making NLG techniques adaptable by the user, i.e., providing users with control over the user model and the hypertext adaptivity.     

Retrieving information from hypertext: issues and problems

One of the most important developments in information science and in information systems in recent years has been the emergence of hypertext as a way of organizing information. Hypertext uses a browsing rather than a searching strategy and hypertext systems have found applications in a number of diverse areas. One of the strengths of using a hypertext system is the freedom it gives to users in the choice of information they wish to see, but this is also one of its drawbacks. This paper examines the effectiveness of hypertext as a way of retrieving information and reviews conventional information retrieval techniques which are the alternative strategy. Previous attempts at combining information retrieval and hypertext are considered and a prototype system outlined which has been developed to generate guided tours for users, to direct them through a hypertext to information they have requested. Finally, how adding this kind of intelligent guidance to a hypertext system would affect its usability as an information system is discussed.     

Hypadapter: An adaptive hypertext system for exploratory learning and programming

We have developed an adaptive hypertext system designed to individually support exploratory learning and programming activities in the domain of Common Lisp. Endowed with domain-specific knowledge represented in a hyperspace of topics, the system builds up a detailed model of the user's expertise which it utilizes to provide personalized assistance. Unlike other work emerging in the field of adaptive hypertext systems, our approach exploits domain and user modelling techniques to support individuals in different ways. The system not only generates individualized presentations of topic nodes, but also provides adaptive navigational assistance for link-based browsing. By identifying and suggesting useful hyperlinks according to the user's knowledge state and preferences, the system encourages and guides exploration. While browsing through the hyperspace of topics, the system analyses the user's navigational behaviour to infer the user's learning progress and to dynamically adapt presentations of topics and links accordingly.     

A glass box approach to adaptive hypermedia

Utilising adaptive interface techniques in the design of systems introduces certain risks. An adaptive interface is not static, but will actively adapt to the perceived needs of the user. Unless carefully designed, these changes may lead to an unpredictable, obscure and uncontrollable interface. Therefore the design of adaptive interfaces must ensure that users can inspect the adaptivity mechanisms, and control their results. One way to do this is to rely on the user's understanding of the application and the domain, and relate the adaptivity mechanisms to domain-specific concepts. We present an example of an adaptive hypertext help system POP, which is being built according to these principles, and discuss the design considerations and empirical findings that lead to this design.     

The Evaluation of a Personalised Health Information System for Patients with Cancer

In this paper we describe the evaluation of a personalised information system for patients with cancer. Our system dynamically generates hypertext pages that explain treatments, diseases, measurements etc related to the patient's condition, using information in the patient's medical record as the basis for the tailoring. We describe results of a controlled trial comparing this system with a nonpersonalised one. The results of the trial slow significant results concerning the patients' preferences for personalised information. We discuss the implications of our evaluation and results for the development and evaluation of future personalised systems, and adaptive hypertext systems in particular.     

Monitoring hypertext users

This paper reports a study to investigate the feasibility of using techniques of learner modelling from intelligent tutoring systems to support users of hypertext systems. The problems of disorientation experienced by hypertext users may be less significant in educationally realistic settings than suggested by previous studies. As a result of our study we conclude that (1) users are rather good at monitoring their own use of a hypertext system and (2) provided that the user's goals and expert paths through the database are both known, then the system, by the overlay modelling technique, may successfully monitor the user's actions.     

Effectiveness of expert semantic knowledge as a navigational aid within hypertext

Hypertext systems parse documents into content nodes connected by machine supported links or relationships. Many hypertext researchers claim that the node-link relationships of hypertext provide an information organization that models the structure of human knowledge and should therefore facilitate information access (Fiderio 1988). Yet, failures of information access occur when users lack an understanding of the overall scope and organization of a hypertext system (Gay and Mazur 1991). To support this understanding, the present research incorporated expert-based domain semantics in the design of prosthetic devices for hypertext navigation. The task domain was documentation for a word processing system. In the first experiment, the pathfinder algorithm (Schvaneveldt 1990) and cluster analysis were used to identify a set of expertbased semantic relationships between word-processing concepts. The results from these analyses contributed to the design of two prostheses to assist hypertext navigation: A hierarchical index and a local semantic browser. These aids were tested in a second experiment, crossing type of on-line documentation (semantically enhanced hypertext or an alphabetically indexed text) with level of subject expertise (novice or expert). Both performance and strategy measures suggest that the semantic prostheses improved the accessibility of information for novice users without hampering expert performance.     

Article Expertext: Intelligent hypertext

Abstract

Intelligent tutoring media can take advantage of hypertext systems and expert systems. Hypertext is text plus an abstraction of the text. In reasoning with this abstraction, a hypertext system manifests expertise. This intelligent hypertext is called expertext. When the abstraction of the text is a semantic network, spreading activation and inheritance methods may help people appreciate the structure of the hypertext. When predicates and implications are included in the abstraction, logical deductions can be performed. Queries can be logically answered and then a sequence of relevant text blocks can be provided as an explanation of the answer. Distributed expertext systems use knowledge bases about the domain of the text and about the users. Distributed expertext systems have been developed which guide people in searching for information and in creating information.     

Information retrieval and hypertext: competing technologies or complementary access methods

Abstract. Information retrieval typically involves accessing textual information from a database in response to a user's vague information need. Hypertext or hypermedia, on the other hand, involves a user browsing through a database of textual or multimedia information in response to a variety of types of information need. Thus information retrieval can be said to have a searching metaphor while hypertext has a browsing analogy. Initially, these two technologies for information access appear to be very different, almost competitive in nature. In this paper information retrieval systems are briefly reviewed and hypertext systems are also examined. These two techniques for accessing information have been integrated into a prototype system which is described. The system dynamically generates guided tours in response to a user's query and the tour guides the user through the hypertext. Some experiments reporting on the effectiveness of this as an information access strategy are given.     

Effectiveness of expert semantic knowledge as a navigational aid within hypertext

Hypertext systems parse documents into content nodes connected by machine supported links or relationships. Many hypertext researchers claim that the node-link relationships of hypertext provide an information organization that models the structure of human knowledge and should therefore facilitate information access (Fiderio 1988). Yet, failures of information access occur when users lack an understanding of the overall scope and organization of a hypertext system (Gay and Mazur 1991). To support this understanding, the present research incorporated expert-based domain semantics in the design of prosthetic devices for hypertext navigation. The task domain was documentation for a word processing system. In the first experiment, the pathfinder algorithm (Schvaneveldt 1990) and cluster analysis were used to identify a set of expertbased semantic relationships between word-processing concepts. The results from these analyses contributed to the design of two prostheses to assist hypertext navigation: A hierarchical index and a local semantic browser. These aids were tested in a second experiment, crossing type of on-line documentation (semantically enhanced hypertext or an alphabetically indexed text) with level of subject expertise (novice or expert). Both performance and strategy measures suggest that the semantic prostheses improved the accessibility of information for novice users without hampering expert performance.     

Interacting With Hypertext: A Meta-Analysis of Experimental Studies

The meta-analysis compared and synthesized the results of 23 experimental studies on hypertext. The analysis was based on 56 pairs of effect sizes and significance levels of the impact of users, tasks, and tools on interactions with hypertext. This analysis focused on three factors that prevailingly influence the use of hypertext: the cognitive styles and spatial ability of users; the complexity of tasks; and the structure of information organization and the visualization of the structure. The meta-analysis found that this group of experimental studies reported significantly discrepant findings, indicating that substantial differences exist among individual experiments. Individual differences in cognition did not yield enough evidence to conclude that the effect sizes are significantly apart from zero. The meta-analysis showed that the overall performance of hypertext users tended to be more effective than that of nonhypertext users, but the differences in efficiency measures were consistently in favor of nonhypertext users. Users benefited more from hypertext tools for open tasks. Overall, the complexity of tasks has the largest combined effect sizes. Graphical maps that visualize the organization of hypertext have significant impact on the usefulness of a hypertext system. This meta-analysis raised two issues concerned with the present hypertext literature: (a) the absence of a taxonomy of tasks for analyzing and comparing hypertext usability across studies, and (b) the weaknesses of the connections between abstract hypertext reference models and specific hypertext systems. These weaknesses may considerably undermine the significance of individual findings on hypertext usability. Results of the meta-analysis suggest that the discrepancies among empirical findings are related to these weaknesses. Future work on hypertext usability should emphasize task taxonomies along with longitudinal and ethnographic studies for a deep understanding of the interactions between users and hypertext. Recommended research issues for the future are highlighted in Section 5.     

一种融合地理位置信息的协同过滤推荐算法

目前,基于用户消费数据构建的推荐系统在电子商务领域发挥着越来越大的作用,而在这些数据中,商家本身具有的地理位置信息忠实地记录了用户的消费痕迹,能够有效反映出用户在地理位置维度上的个人偏好信息,从而对推荐系统具有非常重要的意义。现有工作一般只利用了用户对地点的评价以及地点之间的距离,无法反映出不同地点之间的关联关系,以及用户在不同地点中的偏好权重问题。该文从地理区域划分的角度出发,研究了用户在区域范围内的消费兴趣偏好,以及不同粒度级别的区域划分方法对推荐模型的影响,探索了在推荐过程中有效融合地域信息的方法,考虑了包括地区的全局性影响、用户对地区的偏好等,结合这些因素提出了融合地理位置信息的推荐模型LGE、LGN及LRSVD。通过在Yelp数据集上的实验表明,这些模型相比于传统的推荐算法能够有效提高预测效果。     

A novel mobile recommender system for indoor shopping

With the widespread usage of mobile terminals, the mobile recommender system is proposed to improve recommendation performance, using positioning technologies. However, due to restrictions of existing positioning technologies, mobile recommender systems are still not being applied to indoor shopping, which continues to be the main shopping mode. In this paper, we develop a mobile recommender system for stores under the circumstance of indoor shopping, based on the proposed novel indoor mobile positioning approach by using received signal patterns of mobile phones, which can overcome the disadvantages of existing positioning technologies. Especially, the mobile recommender system can implicitly capture users’ preferences by analyzing users’ positions, without requiring users’ explicit inputting, and take the contextual information into consideration when making recommendations. A comprehensive experimental evaluation shows the new proposed mobile recommender system achieves much better user satisfaction than the benchmark method, without losing obvious recommendation performances.     

Task-based method for creating usable hypertext

Although large hypertext documentation systems have many benefits in the commercial world, they can be difficult to build and use. To help overcome both these obstacles, a method under development at Hewlett-Packard assists authors in creating usable hypertext. A Wizard of Oz experiment was done with traditional on-line documentation and hypertext documentation to see what users liked and disliked. The experiment showed the need for a set of hypertext construction rules to ensure usability. Following these rules, and with computer assistance, authors are expected to do a task analysis of users' activities, to identify critical objects and create content nodes for them, to create links between nodes within clearly defined and cognitively justified limits, and to conduct usability tests on the resulting hypertext volume. Whilst this method recognises the importance of good clear writing, the rules and suggested prectices are not primarily about writing or screen design, but about creating a coherent navigational web that ensures success among commercial users of hypertext. The authoring system described in this paper has been developed for the HP Help system, which has been adopted as the common help delivery system for developers of Common Open Systems Environments on Unix-like platforms.     

User preferences for adaptive user interfaces in health information systems

An adaptive user interface requires identification of user requirements. Interface designers and engineers must understand end-user interaction with the system to improve user interface design. A combination of interviews and observations is applied for user requirement analysis in health information systems (HIS). Then, user preferences are categorized in this paper as either data entry, language and vocabulary, information presentation, or help, warning and feedback. The user preferences in these categories were evaluated using the focus group method. Focus group sessions with different types of HIS users comprising medical staff (with and without computer skills) and system administrators identified each user group’s preference for the initial adaptation of the HIS user interface. User needs and requirements must be identified to adapt the interface to users during data entry into the system. System designers must understand user interactions with the system to identify their needs and preferences. Without this, interface design cannot be adapted to users and users will not be comfortable using the system and eventually abandon its use.     

Instance based personalized multi-form image browsing and retrieval

It is important to adapt and personalize image browsing and retrieval systems based on users’ preferences for improved user experience and satisfaction. In this paper, we present a novel instance based personalized multi-form image representation with implicit relevance feedback and adaptive weighting approach for image browsing and retrieval systems. In the proposed system, images are grouped into forms, which represent different information on images such as location, content etc. We conducted user interviews on image browsing, sharing and retrieval systems for understanding image browsing and searching behaviors of users. Based on the insights gained from the user interview study we propose an adaptive weighting method and implicit relevance feedback for multi-form structures that aim to improve the efficiency and accuracy of the system. Statistics of the past actions are considered for modeling the target of the users. Thus, on each iteration weights of the forms are updated adaptively. Moreover, retrieval results are modified according to the users’ preferences on iterations in order to improve personalized user experience. The proposed method has been evaluated and results are illustrated in the paper. It is shown that, satisfactory improvements can be achieved with proposed approaches in the multi-form scheme.     

Using XML for Supplemental Hypertext Support

Our overall research goal is providing hypertext functionality through the WWW to hypertext-unaware information systems with minimal or no changes to the information systems. Information systems dynamically generate their contents and thus require some mapping mechanism to automatically map the generated contents to hypertext constructs (nodes, links, and link markers) instead of hypertext links being hard-coded over static contents. No systematic approach exists, however, for building mapping routines to create useful links that give users direct access to the ISs' primary functionality, give access to metainformation about IS objects, and enable annotation and ad hoc (user-declared) linking. This paper contributes a procedure for analyzing ISs and building mapping routines that supplement information systems with hypertext support. This paper also contributes an eXtensible Markup Language (XML) DTD that declares a set of elements and attributes for representing mapped information in a human-readable, machine-readable, structured, and semantic way. We implemented a prototype to demonstrate the feasibility of using XML to represent mapped information.     

Forgetting techniques for stream-based matrix factorization in recommender systems

Forgetting is often considered a malfunction of intelligent agents; however, in a changing world forgetting has an essential advantage. It provides means of adaptation to changes by removing effects of obsolete (not necessarily old) information from models. This also applies to intelligent systems, such as recommender systems, which learn users’ preferences and predict future items of interest. In this work, we present unsupervised forgetting techniques that make recommender systems adapt to changes of users’ preferences over time. We propose eleven techniques that select obsolete information and three algorithms that enforce the forgetting in different ways. In our evaluation on real-world datasets, we show that forgetting obsolete information significantly improves predictive power of recommender systems.     

Social group recommendation in the tourism domain

Recommender Systems learn users’ preferences and tastes in different domains to suggest potentially interesting items to users. Group Recommender Systems generate recommendations that intend to satisfy a group of users as a whole, instead of individual users. In this article, we present a social based approach for recommender systems in the tourism domain, which builds a group profile by analyzing not only users’ preferences, but also the social relationships between members of a group. This aspect is a hot research topic in the recommender systems area. In addition, to generate the individual and group recommendations our approach uses a hybrid technique that combines three well-known filtering techniques: collaborative, content-based and demographic filtering. In this way, the disadvantages of one technique are overcome by the others. Our approach was materialized in a recommender system named Hermes, which suggests tourist attractions to both individuals and groups of users. We have obtained promising results when comparing our approach with classic approaches to generate recommendations to individual users and groups. These results suggest that considering the type of users’ relationship to provide recommendations to groups leads to more accurate recommendations in the tourism domain. These findings can be helpful for recommender systems developers and for researchers in this area.