Search (9 results, page 1 of 1)

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Abstract

A commonly used technique for improving search engine performance is result caching. In result caching, precomputed results (e.g., URLs and snippets of best matching pages) of certain queries are stored in a fast-access storage. The future occurrences of a query whose results are already stored in the cache can be directly served by the result cache, eliminating the need to process the query using costly computing resources. Although other performance metrics are possible, the main performance metric for evaluating the success of a result cache is hit rate. In this work, we present a machine learning approach to improve the hit rate of a result cache by facilitating a large number of features extracted from search engine query logs. We then apply the proposed machine learning approach to static, dynamic, and static-dynamic caching. Compared to the previous methods in the literature, the proposed approach improves the hit rate of the result cache up to 0.66%, which corresponds to 9.60% of the potential room for improvement.

Type

a

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Abstract

The recent explosion of the Internet and the WWW has made digital libraries popular. Easy access to a digital library is provided by commercially available Web browsers, which provide a user-friendly interface. To retrieve documents of interest, the user is provided with a search interface that may only consist of one input field and one push button. Most users type in a single keyword, click the button, and hope for the best. The result of a query using this kind of search interface can consist of a large unordered set of documents, or a ranked list of documents based on the freuqency of the keywords. Both lists can contain articles unrelated to the user's inquiry unless a sophisticated search was performed and the user knows exactly what to look for. More sophisticated algorithms for ranking the search results according to how well they meet the users needs as expressed in the search input may help. However, what is desperately needed are software tools that can analyze the search result and manipulate large hierarchies of data graphically. In this article we describe the design of a language-independent document classification systems being developed to help users of the Florida Center for Library Automation analyze search query results. Easy access through the Web is provided, as well as a graphical user interface to display the classification results. We also describe the use of this system to retrieve and analyze sets of documents from public Web sites

Content

"We use the term 'classification' to denote the general process of identifying the subject matter of a document. We use the term 'clustering' to refer to the process of forming groups (clusters) of documents with related topics and subtopics, and visualizing those clusters"

Type

a

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Abstract

The interdisciplinary field known as digital humanities (DH) is represented in various forms in the teaching and research practiced in iSchools. Building on the work of an iSchools organization committee charged with exploring digital humanities curricula, we present findings from a series of related studies exploring aspects of DH teaching, education, and research in iSchools, often in collaboration with other units and disciplines. Through a survey of iSchool programs and an online DH course registry, we investigate the various education models for DH training found in iSchools, followed by a detailed look at DH courses and curricula, explored through analysis of course syllabi and course descriptions. We take a brief look at collaborative disciplines with which iSchools cooperate on DH research projects or in offering DH education. Next, we explore DH careers through an analysis of relevant job advertisements. Finally, we offer some observations about the management and administrative challenges and opportunities related to offering a new iSchool DH program. Our results provide a snapshot of the current state of digital humanities in iSchools which may usefully inform the design and evolution of new DH programs, degrees, and related initiatives.

Series

JASIST special issue on digital humanities (DH): A. Landscapes of DH

Type

a

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Abstract

Information behavior and practices (IBP) research has been repeatedly criticized for having little impact on information systems development (ISD). Claiming that there is a complete disconnect would be an exaggeration but it is apparent that it is not always easy to translate findings of IBP research to workable design recommendations. Based on a reading of earlier literature and a closer investigation of three illustrative example contexts, this article underlines that the value of IBP research for ISD lies in its capability to inform ISD of the variety of ways people deal with information beyond individual systems, their own wants and designers' assumptions. Moreover, it highlights that the implications of information systems go beyond their primary users. Instead of overemphasizing the contextuality of findings, a part of IBP research would benefit from an increased focus on explicating its epistemological extents and limits and identifying, which findings are transferable, what distinguishes specific contexts, what are their defining constraints and priorities, and what aspects of their uniqueness are assumptions and simple clichés.

Type

a

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Abstract

Applying text mining techniques to legal issues has been an emerging research topic in recent years. Although some previous studies focused on assisting professionals in the retrieval of related legal documents, they did not take into account the general public and their difficulty in describing legal problems in professional legal terms. Because this problem has not been addressed by previous research, this study aims to design a text-mining-based method that allows the general public to use everyday vocabulary to search for and retrieve criminal judgments. The experimental results indicate that our method can help the general public, who are not familiar with professional legal terms, to acquire relevant criminal judgments more accurately and effectively.

Type

a

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Abstract

In this paper, we present a case study of how well subject metadata (comprising headings from an international classification scheme) has been deployed in a national data catalogue, and how often data seekers use subject metadata when searching for data. Through an analysis of user search behaviour as recorded in search logs, we find evidence that users utilise the subject metadata for data discovery. Since approximately half of the records ingested by the catalogue did not include subject metadata at the time of harvest, we experimented with automatic subject classification approaches in order to enrich these records and to provide additional support for user search and data discovery. Our results show that automatic methods work well for well represented categories of subject metadata, and these categories tend to have features that can distinguish themselves from the other categories. Our findings raise implications for data catalogue providers; they should invest more effort to enhance the quality of data records by providing an adequate description of these records for under-represented subject categories.

Type

a

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Abstract

Resource Description and Access (RDA) stipulates that certain "core" elements should always be included, where applicable, in bibliographic and authority records, due to their importance in supporting the user tasks defined in Functional Requirements for Bibliographic Records. However, the elements' relative importance has not been empirically tested. This study investigates which elements in bibliographic records are currently most used in a university library catalog, by means of think-aloud sessions conducted by expert and non-expert users, who were assigned sets of typical bibliographic tasks. The results indicate that, in this context at least, the most utilized elements are not all core.

Type

a

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Abstract

The current research explores how intermediaries seek information from patrons, in particular by analyzing intermediaries' elicitation utterances through three dimensions-linguistic forms, utterance purposes, and communicative functions-to determine whether indeed any dimension appeared consistently, to be called "elicitation styles." Five intermediaries from four academic libraries (three national university libraries, one private university library) and one research institute library participated in the study. Thirty patrons with 30 genuine search requests were recruited; thus, 30 patron/intermediary information retrieval interactions making a total of 30 encounters were collected. Video/audio data were taped. Dialogues between patron and intermediary were transcribed. Statistical analysis revealed three types of elicitation styles among the five intermediaries, labeled, (1) situationally oriented, (2) functionally oriented, and (3) stereotyped. This study seeks an explanation for different elicitation styles. Qualitative analysis was applied to investigate "inquiring minds." An inquiring mind is termed to represent a mentality or tendency that one elicits certain threads of questions influenced by Professional beliefs, individual characteristics, tasks, goals, and interactional contexts in conversation. The results of qualitative analysis specified three modes of inquiring minds of the intermediaries, namely: (1) information problem detection, (2) query formulation process, and (3) database instructions.

Type

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