Adaptive Product Manuals

Author(s):  
D T Pham ◽  
R M Setchi

This paper extends the concept of Intelligent Product Manuals (IPMs) which provide just-in-time support to users during the life of the product. The paper advocates the concept of Adaptive Product Manuals (APMs) that generate virtual documents corresponding to the current information needs of users. The key elements of this concept are specification of user information needs, development of a knowledge-based (KB) system with models and algorithms for processing of user requests and generation of active Web pages matching user profiles and information goals.

Author(s):  
D T Pham ◽  
S S Dimov ◽  
B J Peat

Intelligent product manuals are designed to allow product users to utilize a product as easily, effectively and with as little additional care as possible while minimizing support costs for manufacturers and suppliers. It is first shown how intelligent product manuals address these objectives by utilizing electronic, multimedia and knowledge-based technologies to provide active assistance to the user of the product during tasks such as installation, operation and maintenance. An architecture for the creation and deployment of an intelligent product manual is then proposed and general design considerations are outlined. Finally, four implementation approaches, based on XML, SGML, HTML and PDF technologies, are compared against a set of selection criteria. It is concluded that simple, low-cost solutions are available, which can provide significant benefits for appropriate businesses, including smaller companies.


Author(s):  
Li Weigang ◽  
Wu Man Qi

This chapter presents a study of Ant Colony Optimization (ACO) to Interlegis Web portal, Brazilian legislation Website. The approach of AntWeb is inspired by ant colonies foraging behavior to adaptively mark the most significant link by means of the shortest route to arrive the target pages. The system considers the users in the Web portal as artificial ants and the links among the pages of the Web pages as the researching network. To identify the group of the visitors, Web mining is applied to extract knowledge based on preprocessing Web log files. The chapter describes the theory, model, main utilities and implementation of AntWeb prototype in Interlegis Web portal. The case study shows Off-line Web mining; simulations without and with the use of AntWeb; testing by modification of the parameters. The result demonstrates the sensibility and accessibility of AntWeb and the benefits for the Interlegis Web users.


2018 ◽  
Vol 6 (3) ◽  
pp. 67-78
Author(s):  
Tian Nie ◽  
Yi Ding ◽  
Chen Zhao ◽  
Youchao Lin ◽  
Takehito Utsuro

The background of this article is the issue of how to overview the knowledge of a given query keyword. Especially, the authors focus on concerns of those who search for web pages with a given query keyword. The Web search information needs of a given query keyword is collected through search engine suggests. Given a query keyword, the authors collect up to around 1,000 suggests, while many of them are redundant. They classify redundant search engine suggests based on a topic model. However, one limitation of the topic model based classification of search engine suggests is that the granularity of the topics, i.e., the clusters of search engine suggests, is too coarse. In order to overcome the problem of the coarse-grained classification of search engine suggests, this article further applies the word embedding technique to the webpages used during the training of the topic model, in addition to the text data of the whole Japanese version of Wikipedia. Then, the authors examine the word embedding based similarity between search engines suggests and further classify search engine suggests within a single topic into finer-grained subtopics based on the similarity of word embeddings. Evaluation results prove that the proposed approach performs well in the task of subtopic classification of search engine suggests.


2007 ◽  
Vol 33 (1) ◽  
pp. 63-103 ◽  
Author(s):  
Dina Demner-Fushman ◽  
Jimmy Lin

The combination of recent developments in question-answering research and the availability of unparalleled resources developed specifically for automatic semantic processing of text in the medical domain provides a unique opportunity to explore complex question answering in the domain of clinical medicine. This article presents a system designed to satisfy the information needs of physicians practicing evidence-based medicine. We have developed a series of knowledge extractors, which employ a combination of knowledge-based and statistical techniques, for automatically identifying clinically relevant aspects of MEDLINE abstracts. These extracted elements serve as the input to an algorithm that scores the relevance of citations with respect to structured representations of information needs, in accordance with the principles of evidence-based medicine. Starting with an initial list of citations retrieved by PubMed, our system can bring relevant abstracts into higher ranking positions, and from these abstracts generate responses that directly answer physicians' questions. We describe three separate evaluations: one focused on the accuracy of the knowledge extractors, one conceptualized as a document reranking task, and finally, an evaluation of answers by two physicians. Experiments on a collection of real-world clinical questions show that our approach significantly outperforms the already competitive PubMed baseline.


2021 ◽  
Author(s):  
Robin T Higashi ◽  
John W Sweetenham ◽  
Aimee D Israel ◽  
Jasmin A Tiro

BACKGROUND The COVID-19 pandemic created an urgent need to rapidly disseminate health information, especially to those with cancer because they face higher morbidity and mortality rates. At the same time, the disproportionate impact of the pandemic on Latinx populations underscores the need for information to reach Spanish-speakers. However, the equity of information about COVID-19 to Spanish-speaking cancer patients communicated through institutions’ online media is unknown. OBJECTIVE We conducted a multi-modal, mixed method document review study to evaluate the equity of online information about COVID-19 and cancer available to English and Spanish speaking populations from seven healthcare institutions in North Texas, where one in five adults is Spanish-speaking. Our focus is less on the “digital divide”, which conveys disparities in access to computers and the Internet based on the race/ethnicity, education, and income of at-risk populations; rather, our study asks: to what extent is online content useful and culturally appropriate in meeting Spanish-speakers’ information needs? METHODS We reviewed 50 websites (33 English, 17 Spanish) over a period of one week in mid-May 2020. We sampled seven institutions’ main oncology and COVID web pages, as well as both internal (institutional web pages) and external (non-institutional web pages) linked content. We conducted several analyses for each sampled page: (a) thematic content analysis, (b) literacy level analysis using Readability Studio software, (c) coding using the Patient Education and Materials Assessment Tool (PEMAT), and (d) descriptive analysis of video and diversity content. RESULTS The themes most frequently addressed on English and Spanish websites differed somewhat. While “resources/FAQs” were frequently cited themes on both websites, English websites more frequently addressed “news/updates” and “cancer+COVID”, whereas Spanish websites addressed “protection” and “COVID data”. Spanish websites were on average lower literacy (11th grade) than English (13th grade), although still far above recommended guidelines of <9th grade. The overall average accessibility score using the PEMAT analysis was the same for English (n=33 pages) and Spanish pages (n=17 pages) at 82%. Among the DFW organizations, the average accessibility of the Spanish pages (n=7) was slightly lower than that of the English pages (n=19) at 77% vs. 81%, respectively, due mostly to the discrepancy in English-only videos and visual aids. Twelve of the 50 websites (24%) had embedded videos in them, however 100% of videos were in English, including one that was on a Spanish website. CONCLUSIONS We identified an uneven response among the seven healthcare institutions to providing equitable information to Spanish-speaking DFW residents concerned about COVID and cancer. Spanish-speakers lack equal access in both diversity of content about COVID-19 and access to other websites, leaving an already vulnerable cancer patient population at greater risk. We recommend several specific actions to enhance content and navigability for Spanish-speakers.


Symmetry ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1772
Author(s):  
Amit Kumar Nandanwar ◽  
Jaytrilok Choudhary

Internet technologies are emerging very fast nowadays, due to which web pages are generated exponentially. Web page categorization is required for searching and exploring relevant web pages based on users’ queries and is a tedious task. The majority of web page categorization techniques ignore semantic features and the contextual knowledge of the web page. This paper proposes a web page categorization method that categorizes web pages based on semantic features and contextual knowledge. Initially, the GloVe model is applied to capture the semantic features of the web pages. Thereafter, a Stacked Bidirectional long short-term memory (BiLSTM) with symmetric structure is applied to extract the contextual and latent symmetry information from the semantic features for web page categorization. The performance of the proposed model has been evaluated on the publicly available WebKB dataset. The proposed model shows superiority over the existing state-of-the-art machine learning and deep learning methods.


2018 ◽  
Vol 7 (2) ◽  
pp. 849
Author(s):  
Sipra Sahoo ◽  
Bikram Kesari Ratha

The user experience is enhanced by the Web Personalization System (WPS), which depends on the User's Interests (UI) and references are stored in the User Profile (UP). The profiles should be able to adapt and reproduce the change of user’s behavior for such system. Existing web page Recommendation Systems (RS) are still limited by several problems, some of which are the problem of recommending web pages to a new user whose browsing history is not available (Cold Start), sparse data structures (Sparsity), and the problem of over-specialization. In this paper, the UI has been tracked and Dynamic User Profiles have been maintained by introducing a method called Density-Based Spa-tial Clustering of Applications with Noise-User Profiling (DBSCAN-UP). The mapping web pages, construct the ontological concepts, which represent the UI, and the interests of users are learned by the reference ontology, which are used to map the visited web pages. The process of storage, management and adaptation of UI is facilitated by multi-agent system. The different user browsing behaviors learning and adapting capability is built in the proposed system and the efficiency of the DBSCAN-UP model is evaluated by the series of experi-ments. The accuracy of the DBSCAN-UP was achieved up to 5% compared to the existing methods.


Author(s):  
Udo Richard Averweg

Organisations are being forced to invest heavily in the deployment of information systems (IS) to obtain value and benefit in the new knowledge-based environment. Organisational intranets are being used as the platform for developing and deploying critical business applications to support business operations and managerial decision-making across the Internet-worked enterprise. Executive Information Systems (EIS) grew out of the information needs of executives. Web-based technologies are causing a revisit to existing information technology (IT) implementation models, including those for EIS. Some technologies include intranet, Internet, extranet, e-commerce business-to-business (B2B), e-commerce business-to-consumer (B2C), wireless application protocol (WAP), including other mobile technologies. The author conducted a survey of 31 well-established organisations in KwaZulu-Natal, South Africa, which successfully implemented EIS. A validated survey instrument was administered to an EIS stakeholder in each organisation surveyed to rank Web-based technologies in order of their perceived impact on EIS implementation in organisations surveyed. The author reports that an organisational intranet has the highest level of impact on EIS implementation in organisations surveyed in KwaZulu-Natal, South Africa. Given this impact, justifying investment in such IS and IT should be carefully evaluated and quantified.


Sign in / Sign up

Export Citation Format

Share Document