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Techniques for Improving Uniformity in Direct Mapped Caches

Description: Directly mapped caches are an attractive option for processor designers as they combine fast lookup times with reduced complexity and area. However, directly-mapped caches are prone to higher miss-rates as there are no candidates for replacement on a cache miss, hence data residing in a cache set would have to be evicted to the next level cache. Another issue that inhibits cache performance is the non-uniformity of accesses exhibited by most applications: some sets are under-utilized while others receive the majority of accesses. This implies that increasing the size of caches may not lead to proportionally improved cache hit rates. Several solutions that address cache non-uniformity have been proposed in the literature. These techniques have been proposed over the past decade and each proposal independently claims the benefit of reduced conflict misses. However, because the published results use different benchmarks and different experimental setups, (there is no established frame of reference for comparing these results) it is not easy to compare them. In this work we report a side-by-side comparison of these techniques. Finally, we propose and Adaptive-Partitioned cache for multi-threaded applications. This design limits inter-thread thrashing while dynamically reducing traffic to heavily accessed sets.
Date: May 2011
Creator: Nwachukwu, Izuchukwu Udochi
Partner: UNT Libraries

Automatic Indexing: A State-of-the-Art Report

Description: Report issued by the U.S. National Bureau of Standards discussing results of a survey conducted on automatic mechanized indexing and data processing. As stated in the introduction, "it has concentrated on the major developments in and related demonstrations of automatic indexing potentialities. Examples are also given of indexes compiled by machine and of potentially related research efforts in such areas as natural language text searching, statistical association techniques used for search and retrieval, and proposed systems for concept processing" (p. 1). This report includes an illustration.
Date: February 1970
Creator: Stevens, Mary Elizabeth
Partner: UNT Libraries Government Documents Department

Keywords in the mist: Automated keyword extraction for very large documents and back of the book indexing.

Description: This research addresses the problem of automatic keyphrase extraction from large documents and back of the book indexing. The potential benefits of automating this process are far reaching, from improving information retrieval in digital libraries, to saving countless man-hours by helping professional indexers creating back of the book indexes. The dissertation introduces a new methodology to evaluate automated systems, which allows for a detailed, comparative analysis of several techniques for keyphrase extraction. We introduce and evaluate both supervised and unsupervised techniques, designed to balance the resource requirements of an automated system and the best achievable performance. Additionally, a number of novel features are proposed, including a statistical informativeness measure based on chi statistics; an encyclopedic feature that taps into the vast knowledge base of Wikipedia to establish the likelihood of a phrase referring to an informative concept; and a linguistic feature based on sophisticated semantic analysis of the text using current theories of discourse comprehension. The resulting keyphrase extraction system is shown to outperform the current state of the art in supervised keyphrase extraction by a large margin. Moreover, a fully automated back of the book indexing system based on the keyphrase extraction system was shown to lead to back of the book indexes closely resembling those created by human experts.
Date: May 2008
Creator: Csomai, Andras
Partner: UNT Libraries

A Framework of Automatic Subject Term Assignment: An Indexing Conception-Based Approach

Description: The purpose of dissertation is to examine whether the understandings of subject indexing processes conducted by human indexers have a positive impact on the effectiveness of automatic subject term assignment through text categorization (TC). More specifically, human indexers' subject indexing approaches or conceptions in conjunction with semantic sources were explored in the context of a typical scientific journal article data set. Based on the premise that subject indexing approaches or conceptions with semantic sources are important for automatic subject term assignment through TC, this study proposed an indexing conception-based framework. For the purpose of this study, three hypotheses were tested: 1) the effectiveness of semantic sources, 2) the effectiveness of an indexing conception-based framework, and 3) the effectiveness of each of three indexing conception-based approaches (the content-oriented, the document-oriented, and the domain-oriented approaches). The experiments were conducted using a support vector machine implementation in WEKA (Witten, & Frank, 2000). The experiment results pointed out that cited works, source title, and title were as effective as the full text, while keyword was found more effective than the full text. In addition, the findings showed that an indexing conception-based framework was more effective than the full text. Especially, the content-oriented and the document-oriented indexing approaches were found more effective than the full text. Among three indexing conception-based approaches, the content-oriented approach and the document-oriented approach were more effective than the domain-oriented approach. In other words, in the context of a typical scientific journal article data set, the objective contents and authors' intentions were more focused that the possible users' needs. The research findings of this study support that incorporation of human indexers' indexing approaches or conception in conjunction with semantic sources has a positive impact on the effectiveness of automatic subject term assignment.
Date: December 2006
Creator: Chung, EunKyung
Partner: UNT Libraries

Building an Intelligent Filtering System Using Idea Indexing

Description: The widely used vector model maintains its popularity because of its simplicity, fast speed, and the appeal of using spatial proximity for semantic proximity. However, this model faces a disadvantage that is associated with the vagueness from keywords overlapping. Efforts have been made to improve the vector model. The research on improving document representation has been focused on four areas, namely, statistical co-occurrence of related items, forming term phrases, grouping of related words, and representing the content of documents. In this thesis, we propose the idea-indexing model to improve document representation for the filtering task in IR. The idea-indexing model matches document terms with the ideas they express and indexes the document with these ideas. This indexing scheme represents the document with its semantics instead of sets of independent terms. We show in this thesis that indexing with ideas leads to better performance.
Date: August 2003
Creator: Yang, Li
Partner: UNT Libraries

Image manipulation and user-supplied index terms.

Description: This study investigates the relationships between the use of a zoom tool, the terms they supply to describe the image, and the type of image being viewed. Participants were assigned to two groups, one with access to the tool and one without, and were asked to supply terms to describe forty images, divided into four categories: landscape, portrait, news, and cityscape. The terms provided by participants were categorized according to models proposed in earlier image studies. Findings of the study suggest that there was not a significant difference in the number of terms supplied in relation to access to the tool, but a large variety in use of the tool was demonstrated by the participants. The study shows that there are differences in the level of meaning of the terms supplied in some of the models. The type of image being viewed was related to the number of zooms and relationships between the type of image and the number of terms supplied as well as their level of meaning in the various models from previous studies exist. The results of this study provide further insight into how people think about images and how the manipulation of those images may affect the terms they assign to describe images. The inclusion of these tools in search and retrieval scenarios may affect the outcome of the process and the more collection managers know about how people interact with images will improve their ability to provide access to the growing amount of pictorial information.
Date: May 2009
Creator: Schultz, Leah
Partner: UNT Libraries

Indexing Guidelines to Support Z39.50 Profile Searches

Description: This document provides guidelines for indexing MARC 21 records to support a set of searches using Z39.50. The Z39.50 Interoperability Testbed Project (Z-Interop) uses these guidelines to index the 400,000 MARC 21 records that comprise the Z-Interop reference implementation of the Z39.50 server and online catalog.
Date: February 1, 2002
Creator: Moen, William E.
Partner: UNT College of Information

Creating Radioactive MARC Records and Z Queries Using the MARCdocs Database

Description: This document describes how the authors can extend a relational database of MARC documentation to store the appropriate information that will support the automatic generation of the special, diagnostic MARC records the authors will call radioactive MARC (RadMARC) records. The information contained in the database will also support the generation of the Z queries used in the interoperability testing.
Date: December 2, 2004
Creator: Moen, William E.
Partner: UNT College of Information

Z-Interop Interoperability Testing Policies and Procedures: Phase 1 Testing

Description: This document provides an overview and the details of policies and procedures of the Z39.50 Interoperability Testbed Project (referred to as Z-Interop). Specifically, the document lays out the responsibilities and obligations of the Z-Interop testbed and the organizations that participate in interoperability testing. For purposes of this document, Z-Interop staff refers to all members of the Z39.50 Interoperability Testbed Project. Z-Interop participant refers to an individual or organization who tests its Z39.50 client or Z39.50 server through the Z39.50 Interoperability Testbed.
Date: February 1, 2002
Creator: Moen, William E.
Partner: UNT College of Information