37914154
Collaborative relevance judgment: A group consensus method for evaluating user search performance
Relevance judgment has traditionally been considered a personal and subjective matter. A user's search and the search result are treated as an isolated event. To consider the collaborative nature of information retrieval (IR) in a group/organization or even societal context, this article proposes a method that measures relevance based on group/peer consensus. The method can be used in IR experiments. In this method, the relevance of a document is decided by group consensus, or more specifically, by the number of users (or experiment participants) who retrieve it for the same search question. The more users who retrieve it, the more relevant the document will be considered. A user's search performance can be measured by a relevance score based on this notion. The article reports the results of an experiment using this method to compare the search performance of different types of users. Related issues with the method and future directions are also discussed.
62769950
Assessment of the effects of user characteristics on mental models of information retrieval systems
This article reports the results of a study that investigated effects of four user characteristics on users' mental models of information retrieval systems: educational and professional status, first language, academic background, and computer experience. The repertory grid technique was used in the study. Using this method, important components of information retrieval systems were represented by nine concepts, based on four IR experts' judgments. Users' mental models were represented by factor scores that were derived from users' matrices of concept ratings on different attributes of the concepts. The study found that educational and professional status, academic background, and computer experience had significant effects in differentiating users on their factor scores. First language had a borderline effect, but the effect was not significant enough at α = 0.05 level. Specific different views regarding IR systems among different groups of users are described and discussed. Implications of the study for information science and IR system designs are suggested.
206955905
Design of symmetric orthonormal wavelet filters using a single complex allpass filter
This paper gives a new class of real-valued symmetric orthonormal wavelet filters by using a single complex allpass filter. Firstly, the conditions that the complex allpass filter has to satisfy are derived from the symmetric and orthonormal conditions of wavelets. Then, from the viewpoint of the wavelet regularity, a new method is proposed for designing the proposed symmetric orthonormal wavelet filters with maximal flatness. In the proposed method, the maximally flat solutions can be easily obtained by solving a set of linear equations only.
2953976
A performance study of monitoring and information services for distributed systems
Monitoring and information services form a key component of a distributed system, or Grid. A quantitative study of such services can aid in understanding the performance limitations, advise in the deployment of the monitoring system, and help evaluate future development work. To this end, we study the performance of three monitoring and information services for distributed systems: the Globus Toolkit/spl reg/ Monitoring and Discovery Service (MDS2), the European Data Grid Relational Grid Monitoring Architecture (R-GMA) and Hawkeye, part of the Condor project. We perform experiments to test their scalability with respect to number of users, number of resources and amount of data collected. Our study shows that each approach has different behaviors, often due to their different design goals. In the four sets of experiments we conducted to evaluate the performance of the service components under different circumstances, we found a strong advantage to caching or pre-fetching the data, as well as the need to have primary components at well-connected sites because of the high load seen by all systems.
750246
Noise Tolerance of EP-Based Classifiers
Emerging Pattern (EP)-based classifiers are a type of new classifiers based on itemsets whose occurrence in one dataset varies significantly from that of another. These classifiers are very promising and have shown to perform comparably with some popular classifiers. In this paper, we conduct two experiments to study the noise tolerance of EP-based classifiers. A primary concern is to ascertain if overfitting occurs in them. Our results highlight the fact that the aggregating approach in constructing EP-based classifiers prevents them from overfitting. We further conclude that perfect training accuracy does not necessarily lead to overfitting of a classifier as long as there exists a suitable mechanism, such as an aggregating approach, to counterbalance any propensity to overfit.
14856827
Relation-Based Document Retrieval for Biomedical IR
In this paper, we explore the use of term relations in information retrieval for precision-focused biomedical literature search. A relation is defined as a pair of two terms which are semantically and syntactically related to each other. Unlike the traditional “bag-of-word” model for documents, our model represents a document by a set of sense-disambiguated terms and their binary relations. Since document level co-occurrence of two terms, in many cases, does not mean this document addresses their relationships, the direct use of relation may improve the precision of very specific search, e.g. searching documents that mention genes regulated by Smad4. For this purpose, we develop a generic ontology-based approach to extract terms and their relations, and present a betweenness centrality based approach to rank retrieved documents. A prototyped IR system supporting relation-based search is then built for Medline abstract search. We use this novel IR system to improve the retrieval result of all official runs in TREC-2004 Genomics Track. The experiment shows promising performance of relation-based IR. The average P@100 (the precision of top 100 documents) for 50 topics is significantly raised from 26.37 %( the P@100 of the best run is 42.10%) to 53.69% while the MAP (mean average precision) is kept at an above-average level of 26.59%. The experiment also shows the expressiveness of relations for the representation of information needs, especially in the area of biomedical literature full of various biological relations.
736327
A usage-based authorization framework for collaborative computing systems
Collaborative systems such as Grids provide efficient and scalable access to distributed computing capabilities and enable seamless resource sharing between users and platforms. This heterogeneous distribution of resources and the various modes of collaborations that exist between users, virtual organizations, and resource providers require scalable, flexible, and fine-grained access control to pro-tect both individual and shared computing resources. In this paper we propose a usage control (UCON) based authorization frame-work for collaborative applications. In our framework, usage con-trol policies are defined using subject and object attributes, along with system attributes as conditions. General attributes include not only persistent attributes such as role and group memberships, but also mutable usage attributes of subjects and objects. Conditions in UCON can be used to support context-based authorizations in ad-hoc collaborations. As a proof-of-concept we implement a pro-totype system based on our proposed architecture and conduct ex-perimental studies to demonstrate the feasibility and performance of our approach.