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To make good decisions, businesses try to gather good intelligence information. Yet managing and processing a large amount of unstructured information and data stand in the way of greater business knowledge. An effective business intelligence tool must be able to access quality information from a variety of sources in a variety of forms, and it must support people as they search for and analyze that information. The EBizPort system was designed to address information needs for the business/IT community. EBizPort's collection-building process is designed to acquire credible, timely, and relevant information. The user interface provides access to collected and metasearched resources using innovative tools for summarization, categorization, and visualization. The effectiveness, efficiency, usability, and information quality of the EBizPort system were measured. EBizPort significantly outperformed Brint, a business search portal, in search effectiveness, information quality, user satisfaction, and usability. Users particularly liked EBizPort's clean and user-friendly interface. Results from our evaluation study suggest that the visualization function added value to the search and analysis process, that the generalizable collection-building technique can be useful for domain-specific information searching on the Web, and that the search interface was important for Web search and browse support.

Illiteracy is often associated with people in developing countries. However, an estimated 50% of adults in a developed country such as Canada lack the literacy skills required to cope with the challenges of today's society; for them, tasks such as reading, understanding, basic arithmetic, and using everyday items are a challenge. Many community-based organizations offer resources and support for these adults, yet overall functional literacy rates are not improving. This is due to a wide range of factors, such as poor retention of adult learners in literacy programs, obstacles in transferring the acquired skills from the classroom to the real life, personal attitudes towards learning, and the stigma of functional illiteracy. In our research we examined the opportunities afforded by personal mobile devices in providing learning and functional support to low-literacy adults. We present the findings of an exploratory study aimed at investigating the reception and adoption of a technological solution for adult learners. ALEX © is a mobile application designed for use both in the classroom and in daily life in order to help low-literacy adults become increasingly literate and independent. Such a solution complements literacy programs by increasing users' motivation and interest in learning, and raising their confidence levels both in their education pursuits and in facing the challenges of their daily lives. We also reflect on the challenges we faced in designing and conducting our research with two user groups (adults enrolled in literacy classes and in an essential skills program), and contrast the educational impact and attitudes toward such technology between these. Our conclusions present the lessons learnt from our evaluations and the impact of the studies' 1 [PUC EIST Special Issue Template] specific challenges on the outcome and uptake of such mobile assistive technologies in providing practical support to low-literacy adults in conjunction with literacy and essential skills training.

TXTRACTOR is a tool that uses established sentence-selection heuristics to rank text segments, producing summaries that contain a user-defined number of sentences. The purpose of identifying text segments is to maximize topic diversity, which is an adaptation of the Maximal Marginal Relevance criterion used by Carbonell and Goldstein [5]. Sentence selection heuristics are then used to rank the segments. We hypothesize that ranking text segments via traditional sentence-selection heuristics produces a balanced summary with more useful information than one produced by using segmentation alone. The proposed summary is created in a three-step process, which includes 1) sentence evaluation 2) segment identification and 3) segment ranking. As the required length of the summary changes, low-ranking segments can then be dropped from (or higher ranking segments added to) the summary. We compare the output of TXTRACTOR to the output of a segmentation tool based on the TextTiling algorithm to validate the approach.