A Visualization Tool Using PAD++ to Browse Information Structure

Explosive growth in information has led to an information overload. To ease the problem, Meta-Content Format (MCF) was developed by Apple Computers to separate structure from content. Apple also developed a browser, called HotSauce, to browse data encoded in MCF format. We did user evaluations of HotSauce to understand its strengths and weaknesses. Based on these evaluations, we developed a new browser using PAD++. Our browser overcomes some of the deficiencies of HotSauce

A Simulation Model of Document Information Retrieval System with Relevance Feedback

Information retrieval systems are very complex in nature due to the complex interaction of document, query, and matching subsystems involved in the process. Researchers working on developing new techniques to improve system performance typically use standardized document collections to test their techniques. This paper has a twofold objective. First, it presents a simulation model of the document information retrieval system. A simulation model can serve as a test-bed document collection that can be used by researchers in the area to test their techniques. A few experiments are run on this simulated collection to demonstrate the effect of varying queries, documents, and user requirements. Second, relevance feedback is employed in the model whereby the matching function used by the system, to match documents with queries, is progressively adapted to the preference function used by the user to judge relevance of the documents

Disaggregating the Differential Impact of Healthcare IT in Complex Care Delivery: Insights from Field Research in Chronic Care

This study focuses on the impact of digitizing medical information on the efficiency and perceived quality of chronic care delivery at the individual physician level. This study extends the theory of task technology fit to activity systems consisting of highly interdependent tasks. We find that the outcomes of efficiency and quality gains are driven by the structure of interdependencies between tasks that physicians perform. While structured information plays a key role in enabling both decision-making and task execution, we find that physician-created semistructured information is also an important predictor of both efficiency and quality gains. We show that the structure of activity systems (task interdependencies) has a strong moderating influence on the factors that drive efficiency and quality gains. We find that digitization enables physicians to preprocess patients’ records prior to their visit which in turn drives gains in both the efficiency and the perceived quality of care delivered

Some Fixed Point Theorems of Integral Type Satisfies Contraction

In this paper we proof some fixed point theorem for a pair of self maps of integral type which satisfies the contraction mapping. Subject Classification : 54H25, 47H10. Keywords: Lebesgue-integrable map ,complete metric space, Common fixed point

Common Fixed point theorems for contractive maps of Integral type in modular metric spaces

In this theorem we proves a common fixed point theorem for a pair of ?-compatible maps ofintegral type , further generalization is done by the existence of Banach contraction mappingin fixed point theorem in modular metric spaces

Fixed Point and Common Fixed Point Theorems in Vector Metric Spaces

In the present paper we prove fixed point and common fixed point theorems in two self mappings  satisfy quasi type contraction. Keywords :Fixed point, Common Fixed point ,self mapping, vector Metric space , E-complete. Mathematical Subject Classification: 47B60, 54H25

Automatic Generation of Matching Function by Genetic Programming for Effective Information Retrieval

With the advent of the Internet, online resources are increasingly available. Many users choose popular search engines to perform an online search to satisfy their information need. However, these search engines tend to turn up many non-relevant documents, which make their retrieval precision very low. How to find appropriate ranking metrics to retrieve more relevant documents and fewer non-relevant documents for users remains a big challenge to the information retrieval community. In this paper, we propose a new framework that combines the merits of genetic programming and relevance feedback techniques to automatically generate and refine the matching functions used for document ranking. This approach overcomes the shortcoming of traditional ranking algorithms using a fixed ranking strategy. It also gives some new ideas and hints for information retrieval professionals

Personalization of Search Engine Services for Effective Retrieval and Knowledge Management

The Internet and corporate intranets provide far more information than anybody can absorb. People use search engines to find the information they require. However, these systems tend to use only one fixed term weighting strategy regardless of the context to which it applies, posing serious performance problems when characteristics of different users, queries, and text collections are taken into consideration. In this paper, we argue that the term weighting strategy should be context specific, that is, different term weighting strategies should be applied to different contexts, and we propose a new systematic approach that can automatically generate term weighting strategies for different contexts based on genetic programming (GP). The new proposed framework was tested on TREC data and the results are very promising

Fixed point theorems through rational expression in Altering distance functions

In this paper we proves a generalised results of J.R. Morales , E.M.Rojas , B.K.Dasand,  S.Gupta .Also the results given by B.Samet and H.Yazid using altering distance functions and property P for the contraction mappings. Keywords:Fixed point, Altering distance functions, Complete metric space. Mathematical Subject Classification: 45H10, 54H25