A MANAGEMENT INFORMATION SYSTEM AND EVALUATION SCHEME FOR THE UNIVERSITY OF TEXAS EMPLOYEE ASSISTANCE PROGRAMS

Early Employee Assistance Programs (EAPs) had their origin in humanitarian motives, and there was little concern for their cost/benefit ratios; however, as some programs began accumulating data and analyzing it over time, even with single variables such as absenteeism, it became apparent that the humanitarian reasons for a program could be reinforced by cost savings particularly when the existence of the program was subject to justification.^ Today there is general agreement that cost/benefit analyses of EAPs are desirable, but the specific models for such analyses, particularly those making use of sophisticated but simple computer based data management systems, are few.^ The purpose of this research and development project was to develop a method, a design, and a prototype for gathering managing and presenting information about EAPS. This scheme provides information retrieval and analyses relevant to such aspects of EAP operations as: (1) EAP personnel activities, (2) Supervisory training effectiveness, (3) Client population demographics, (4) Assessment and Referral Effectiveness, (5) Treatment network efficacy, (6) Economic worth of the EAP.^ This scheme has been implemented and made operational at The University of Texas Employee Assistance Programs for more than three years.^ Application of the scheme in the various programs has defined certain variables which remained necessary in all programs. Depending on the degree of aggressiveness for data acquisition maintained by program personnel, other program specific variables are also defined. ^

Image Retrieval: The MIRACLE Approach

ImageCLEF is a pilot experiment run at CLEF 2003 for cross language image retrieval using textual captions related to image contents. In this paper, we describe the participation of the MIRACLE research team (Multilingual Information RetrievAl at CLEF), detailing the different experiments and discussing their preliminary results.

Reversible inactivation of the nucleus basalis magnocellularis induces disruption of cortical acetylcholine release and acquisition, but not retrieval, of aversive memories

The basal forebrain complex, which includes the nucleus basalis magnocellularis (NBM), provides widespread cholinergic and γ-aminobutyric acid-containing projections throughout the brain, including the insular and pyriform cortices. A number of studies have implicated the cholinergic neurons in the mediation of learning and memory processes. However, the role of basal forebrain activity in information retrieval mechanisms is less known. The aim of the present study is to evaluate the effects of reversible inactivation of the NBM by tetrodotoxin (TTX, a voltage-sensitive sodium channel blocker) during the acquisition and retrieval of conditioned taste aversion (CTA) and to measure acetylcholine (ACh) release during TTX inactivation in the insular cortex, by means of the microdialysis technique in free-moving rats. Bilateral infusion of TTX in the NBM was performed 30 min before the presentation of gustative stimuli, in either the CTA acquisition trial or retrieval trial. At the same time, levels of extracellular ACh release were measured in the insular cortex. The behavioral results showed significant impairment in CTA acquisition when the TTX was infused in the NBM, whereas retrieval was not affected when the treatment was given during the test trial. Biochemical results showed that TTX infusion into the NBM produced a marked decrease in cortical ACh release as compared with the controls during consumption of saccharin in the acquisition trial. Depleted ACh levels were found during the test trial in all groups except in the group that received TTX during acquisition. These results suggest a cholinergic-dependent process during acquisition, but not during memory retrieval, and that NBM-mediated cholinergic cortical release may play an important role in early stages of learning, but not during recall of aversive memories.

Spoken document retrieval experiments with IR-n system

This paper describes the first participation of IR-n system at Spoken Document Retrieval, focusing on the experiments we made before participation and showing the results we obtained. IR-n system is an Information Retrieval system based on passages and the recognition of sentences to define them. So, the main goal of this experiment is to adapt IR-n system to the spoken document structure by means of the utterance splitter and the overlapping passage technique allowing to match utterances and sentences.

A general proposal to multilingual information access based on syntactic-semantic patterns

In the last few years, there has been a wide development in the research on textual information systems. The goal is to improve these systems in order to allow an easy localization, treatment and access to the information stored in digital format (Digital Databases, Documental Databases, and so on). There are lots of applications focused on information access (for example, Web-search systems like Google or Altavista). However, these applications have problems when they must access to cross-language information, or when they need to show information in a language different from the one of the query. This paper explores the use of syntactic-sematic patterns as a method to access to multilingual information, and revise, in the case of Information Retrieval, where it is possible and useful to employ patterns when it comes to the multilingual and interactive aspects. On the one hand, the multilingual aspects that are going to be studied are the ones related to the access to documents in different languages from the one of the query, as well as the automatic translation of the document, i.e. a machine translation system based on patterns. On the other hand, this paper is going to go deep into the interactive aspects related to the reformulation of a query based on the syntactic-semantic pattern of the request.

Towards a unified framework for opinion retrieval, mining and summarization

The exponential increase of subjective, user-generated content since the birth of the Social Web, has led to the necessity of developing automatic text processing systems able to extract, process and present relevant knowledge. In this paper, we tackle the Opinion Retrieval, Mining and Summarization task, by proposing a unified framework, composed of three crucial components (information retrieval, opinion mining and text summarization) that allow the retrieval, classification and summarization of subjective information. An extensive analysis is conducted, where different configurations of the framework are suggested and analyzed, in order to determine which is the best one, and under which conditions. The evaluation carried out and the results obtained show the appropriateness of the individual components, as well as the framework as a whole. By achieving an improvement over 10% compared to the state-of-the-art approaches in the context of blogs, we can conclude that subjective text can be efficiently dealt with by means of our proposed framework.

The utilitarian and hedonic outcomes of music information seeking in everyday life

This qualitative study focuses on what contributes to making a music information-seeking experience satisfying in the context of everyday life. Data were collected through in-depth interviews conducted with 15 younger adults (18 to 29 years old). The analysis revealed that satisfaction could depend on both hedonic (i.e., experiencing pleasure) and utilitarian outcomes. It was found that two types of utilitarian outcomes contributed to satisfaction: (1) the acquisition of music, and (2) the acquisition of information about music. Information about music was gathered to (1) enrich the listening experience, (2) increase one's music knowledge, and/or (3) optimize future acquisition. This study contributes to a better understanding of music information-seeking behavior in recreational contexts. It also has implications for music information retrieval systems design: results suggest that these systems should be engaging, include a wealth of extra-musical information, allow users to navigate among music items, and encourage serendipitous encountering of music.

The utilitarian and hedonic outcomes of music information seeking in everyday life

This qualitative study focuses on what contributes to making a music information-seeking experience satisfying in the context of everyday life. Data were collected through in-depth interviews conducted with 15 younger adults (18 to 29 years old). The analysis revealed that satisfaction could depend on both hedonic (i.e., experiencing pleasure) and utilitarian outcomes. It was found that two types of utilitarian outcomes contributed to satisfaction: (1) the acquisition of music, and (2) the acquisition of information about music. Information about music was gathered to (1) enrich the listening experience, (2) increase one's music knowledge, and/or (3) optimize future acquisition. This study contributes to a better understanding of music information-seeking behavior in recreational contexts. It also has implications for music information retrieval systems design: results suggest that these systems should be engaging, include a wealth of extra-musical information, allow users to navigate among music items, and encourage serendipitous encountering of music.

GUIDE-O; an experimental information system /

Thesis (M.S.)--University of Illinois at Urbana-Champaign.

State of Illinois labor market information plan, 1986-1987 /

"February 1986."

Arizona mineral-resource data : information available through the U.S. Geological Survey Mineral Resource Data System /

Mode of access: Internet.

Intelligent encoding of concepts in web development retrieval

The main aim of the proposed approach presented in this paper is to improve Web information retrieval effectiveness by overcoming the problems associated with a typical keyword matching retrieval system, through the use of concepts and an intelligent fusion of confidence values. By exploiting the conceptual hierarchy of the WordNet (G. Miller, 1995) knowledge base, we show how to effectively encode the conceptual information in a document using the semantic information implied by the words that appear within it. Rather than treating a word as a string made up of a sequence of characters, we consider a word to represent a concept.

Multi-topic information filtering with a single user profile

In Information Filtering (IF) a user may be interested in several topics in parallel. But IF systems have been built on representational models derived from Information Retrieval and Text Categorization, which assume independence between terms. The linearity of these models results in user profiles that can only represent one topic of interest. We present a methodology that takes into account term dependencies to construct a single profile representation for multiple topics, in the form of a hierarchical term network. We also introduce a series of non-linear functions for evaluating documents against the profile. Initial experiments produced positive results.