Knowledge portals are a method to provide integrated access to users of multiple systems through a single-entry point. A large body of literature exists on knowledge portals; however, the only published literature reviews are outdated, as they only cover material prior to the 21st century. The purpose of this article is to present review on some major papers about knowledge portals that were published from 2000-2017. The review takes a holistic perspective based on systems development life cycle to critique the literature and identifies key challenges that enlighten future directions. Trends in the first decade of the 21st century include the desire to formalize and standardize a model of knowledge portals, while major challenges for the future include the need to maintain cybersecurity across users and platforms.

Decision making in the field of financial management is a very complicated and dynamic process. How to incorporate domain knowledge into evolutionary computing to solve financial decision-making problems has long been an interest of researchers. This paper investigates the use of domain knowledge in an evolutionary process, especially in the mutation process. A semantic network of financial attributes is created and used to measure the variation between parents and offspring introduced in the mutation process. The proposed distance-proportional mutation (DPM) constrains the mutation size to be a) small enough that the searching proceeds gracefully, while b) large enough to avoid being trapped into local optima. The hypothesis is that the DPM outperforms a random mutation or a constrained mutation in which only the component that is the closest to the one being mutated can be selected, and provides a better decision-making support for the stock classification problem. Experiments were implemented to test the hypothesis. DPM is also compared with other classifiers, such as decision trees. The results support the hypothesis and shed light on future directions to further delineate the theory of how evolutionary computation can gradually build on the body of human knowledge.

There has been a plethora of research in the area of knowledge portals, knowledge warehouses, ontologies, ontology creation and mapping, as well as the automatic creation and mapping of ontologies. While research exists in each respective area there is a lack of conceptual models that will integrate ontologies as a tool for disparate data source integration into knowledge portals or enterprise knowledge warehouses. The purpose of this work is to discuss different tools that have been developed in academic research and provide a conceptual model of how to implement these tools in relation to knowledge portals and warehouses.

Machine learning algorithms, such as the genetic algorithm, have often been applied to financial problems, but not enough is known about how to systematically incorporate financial knowledge into these generic learning algorithms. The general hypothesis of this paper is that semantic similarity among financial concepts can be exploited in a hybrid genetic algorithm. A Knowledge-guided Genetic Algorithm for Forecasting is introduced to predict the values of financial statement variables. The mutation operation is guided by domain knowledge to make small or large changes in an organism. The algorithm makes a bigger (or smaller) change in the organism when the variables being forecast have higher (or lower) variability. The specific hypothesis is that the use of problem-specific knowledge improves the prediction accuracy. The experimental results show that the use of domain knowledge improves the performance of the algorithm. The knowledge used in this experiment would reasonably be extended in various ways to be used by a refined genetic algorithm.

We propose an adaptive neuro-fuzzy inference system (ANFIS) for stock portfolio return prediction. Previous work has shown that portfolio optimization can be improved by using predicted stock earnings rather than historical earnings. We show that predicted portfolio returns can be improved by using ANFIS and taking as input a variety of technical and fundamental attributes about various indices of the stock market. To generate membership functions, we use a robust noise rejection-clustering algorithm. The neuro-fuzzy model is tested on portfolios constituted from the Tehran Stock Exchange. In our experiments, the proposed method performs better in predicting the portfolio return than the classical Markowitz portfolio optimization method, a multiple regression, a neural network, and the Sugeno–Yasukawa method. © 2010 Wiley Periodicals, Inc.

This paper presents two studies of the use of the WWW in Scottish universities and American land-grant universities. First, we investigated the relationship between the organisational profile of a university department in Scotland and its structural connectivity on the WWW. A Spearman rank order correlation analysis revealed a number of strong correlation relationships between structural connectivity measures and the organisational profile based on research assessment exercise ratings, teaching quality assessments, student–staff ratios and funding levels. Linkage patterns from 13 Scottish academic sites to commercial sites in Britain and America highlighted the impact of culture and the appropriateness of information technologies on the acceptance of the WWW. The second study is a content survey of WWW-based education activities in American land-grant universities to investigate successful applications of these enabling techniques in education. The two studies together highlighted cultural, political and technological interactions in the use of the WWW.

One important facet of current hypertext research involves using knowledge-based techniques to develop and maintain document structures. A semantic net is one such technique. However, most semantic-net-based hypertext systems leave the linking consistency of the net to individual users. Users without guidance may accidentally introduce structural and relational inconsistencies in the semantic nets. The relational inconsistency hinders the creation of domain information models. The structural inconsistency leads to unstable documents, especially when a document is composed by computation with traversal algorithms. This work tackles to above problems by integrating logical structure and domain semantics into a semantic net. A semantic-net-based structured-hypertext model has been formalized. The model preserves structural and relational consistency after changes to the semantic net. The hypertext system (RICH) based on this model has been implemented and tested. The RICH system can define and enforce a set of rules to maintain to integrity of the semantic net and provide particular support for creating multihierarchies with the reuse of existing contents and structures. Users have found such flexible but enforceable semantics to be helpful.

This panel will discuss major issues and challenges in computer science education across a wide range of institutions. It originates from a report developed by the Education Working Group of the Strategic Directions in Computing Research (SDCR) Workshop. That report appears in its entirety in the ACM Computing Surveys issue [Wegner96] which is distributed to all attendees to this SIGCSE 97 conference.) In this panel, we will discuss the general aims and accomplishments of the SDCR conference, highlighting the specific recommendations of the Education Working Group. We will outline ideas for improving the quality and effectiveness of computer science programs at the undergraduate, graduate, and K-12 levels. We will also argue for the creation of a Resource Center for developing and distributing computer science and engineering curricular materials, including the idea of developing a "Virtual Computing University."

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.

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.

Most electronic publishing systems concentrate on formatting. However, an electronic publishing environment should: (1) support the whole life cycle of publication; (2) be a highly integrated environment; (3) have a hypermedia publishing capability; and (4) be easily extended to deal with new media and support new publishing activities. An electronic publishing environment called MUCH (Many Using and Creating Hypermedia) has been developed that supports collaborative authoring, reuse, formating and printing, management, hypermedia publishing and delivery, and interchange. MUCH is based on public domain tools, such as Andrew, and has been used in the authoring of many lengthy documents. © 1994 John Wiley & Sons, Inc.

This paper presents an SGML-MUCH (S-M) system, the I/O subsystem of a collaborative authoring and reuse system called MUCH (Many Using and Creating Hypermedia), for text and hypertext mutual conversion and hypertext interchange.The S-M system can dynamically generate text documents from the MUCH document database by traversing a subgraph of the hypertext database.With various options on traversal, different versions of documents ean be generated from the same set of nodes and links in the document database.The documents generated from the MUCH document database include not only document content but also groupware and hypertext information that can be used for hypertext interchange.With this generated document, hypertext for different systems such as Guide and Hyperties can be automatically generated and new features, like alternate outline and automatically derived indices can also be incorporated.The S-M system, which was developed using several public-domain development tools, adheres to standards where possible, and generally foeuses on' openness'.

Traditional documents may be transformed into hypertext by first reflecting the document's logical markup in the hypertext (producing first-order hypertext) and then by adding links not evident in the document markup (producing second-order hypertext). In our transformation of a textbook to hypertext, the textbook is placed in an intermediate form based on a semantic net and is then placed into the four hypertext systems: Emacs-Info, Guide, HyperTies, and Super-Book. The first-order Guide and SuperBook hypertexts reflect a depth-first traversal of the semantic net, and the Emacs-Info and HyperTies hypertexts reflect a breadth-first traversal. The semantic net is augmented manually, and then new traversal programs automatically generate alternate outlines. An index based on work patterns in the textbook is also automatically generated for the second-order hypertext. Our suite of programs has been applied to a published textbook, and the resulting hypertexts are publicly available.

Inheritance is commonly, exploited by computer programs that deal with hierarchic knowledge and is one instance of the regularity described in this work. Regularity formalizes the observation that hierarchical relationships between concepts reflect relationships between the concepts' properties, and vice versa. Based on the regularity in a knowledge base, an expansion procedure can compute what the attributes of concepts should be when those attributes haven't been previously discovered. In tangled hierarchies where a concept has several parents, a true-false model of property values cannot capture the complexity of the relationships among property values. Fuzzy representations of regularity and expansion correct this failure. The fuzzy sets framework takes into account the normative nature of property values. A theorem is presented that relates a parameter of the fuzzy expansion algorithm to the reliability of expansion. A computer program that implements expansion has been applied to several medical knowledge bases. The experimental results show that expansion is reliable.>

In contrast with the claims of Bench-Capon and McEnery (1989), this paper argues that users of computer systems will find it more profitable to model the computer system than to model its programmers. However, Bench-Capon and McEnery's views about the limitations of natural language for interacting with computers are supported.

Motivated by the properties of spreading activation and conceptual distance, the authors propose a metric, called distance, on the power set of nodes in a semantic net. Distance is the average minimum path length over all pairwise combinations of nodes between two subsets of nodes. Distance can be successfully used to assess the conceptual distance between sets of concepts when used on a semantic net of hierarchical relations. When other kinds of relationships, like 'cause', are used, distance must be amended but then can again be effective. The judgements of distance significantly correlate with the distance judgements that people make and help to determine whether one semantic net is better or worse than another. The authors focus on the mathematical characteristics of distance that presents novel cases and interpretations. Experiments in which distance is applied to pairs of concepts and to sets of concepts in a hierarchical knowledge base show the power of hierarchical relations in representing information about the conceptual distance between concepts.>

An investigation is reported of ways to take advantage of the semantics in thesauri to improve: (1) indexing by providing descriptions of documents as sets of terms from the thesaurus; and (2) retrieval by assessing the relevance of documents to a query. Thesauri need to be updated to account for the evolution of the field they cover. Accordingly, various augmentation algorithms and methods to assess the usefulness of these augmentations are being studied. The augmentations consist of merging two existing thesauri. By keeping a consistent level of complexity among the structure manipulated by the merging algorithm, the reasoning method, and the evaluation procedure, an improvement of the performance of the merged thesaurus on both document indexing and retrieval is demonstrated.>

A thesaurus can be a critical component of an office information system. Access to various sets of documents can be facilitated by thesauri and by the connections that are made among thesauri. In the projects described in this paper, the thesauri are stored and manipulated through a relational database management system. The system detects inheritance properties in a thesaurus and uses them to guide a human expert in decisions about how to augment the thesaurus. New strategies will extend our ability to augment existing thesauri.

To facilitate knowledge refinement, a system should be designed so that small changes in the knowledge correspond to small changes in the function or performance of the system. Two sets of experiments show the value of small, heuristically guided changes in a weighted rule base. In the first set, the ordering among numbers (reflecting certainties) makes their manipulation more straightforward than the manipulation of relationships. A simple credit assignment and weight adjustment strategy for improving numbers in a weighted, rule-based expert system is presented. In the second set, the rearrangement of predicates benefits from additional knowledge about the ``ordering'' among predicates. A third set of experiments indicates the importance of the proper level of granularity when augmenting a knowledge base. Augmentation of one knowledge base by analogical reasoning from another knowledge base did not work with only binary relationships, but did succeed with ternary relationships. To obtain a small improvement in the knowledge base, a substantial amount of structure had to be treated as a unit.