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Information foraging through clustering and summarization: A self-organizing approach
No full textSuccessful knowledge management requires efficient tools to manage information in the form of text. However, our productivity in generating information has exceeded our ability to process it, and the dream of creating an information-rich society has become a nightmare of information overload. Although researchers and developers believe that interactive information access systems based on clustering and summarization offer a potential remedy to that problem, there is as yet no empirical evidence showing superiority of those tools over traditional keyword search. This dissertation attempted to determine whether automated clustering can help to find relevant information by suggesting an innovative implementation and verifying its potential ability to be of help. Our implementation is based on Kohonen's self-organizing maps and acts as a visualization layer between the user and a keyword-based search engine. We used the clustering properties of self-organizing maps to create a summary of search results. The user relies on this summary when deciding whether and how to provide additional feedback to the system to obtain more relevant documents. We have resolved multiple issues related to the speed and quality of output associated with self-organizing maps and created a version (Adaptive Search) that allows interactive Internet searching. We have performed user studies and a controlled experiment in order to test the proposed approach. In a laboratory experiment, subjects spent less time finding correct answers using Adaptive Search than using the search engine directly. In addition, the documents containing answers were positioned consistently higher in the rank-ordered lists suggested by Adaptive Search as opposed to the lists suggested by the search engine. The search engine that we used was AltaVista, known to be one of the most popular, comprehensive and flexible engines on the Web. Our main conclusion is that indeed information clustering helps information seekers if properly implemented.This item was digitized from a paper original and/or a microfilm copy. If you need higher-resolution images for any content in this item, please contact us at [email protected] file replaced with corrected file September 2023
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
A conceptual model for examining mobile government adoption in Saudi Arabia
No full textRecently, many governments have started to change the ways of providing their services, so they allow their citizens to access services from anywhere, without the need to go to a physical place of the service provider. Mobile government (M-government) is one of the techniques which fulfil that goal and adopted by many governments. Mgovernment can be defined as an implementation of Electronic Government (E-Government), where mobile technology is used, with the aim of improving service delivery to citizens, businesses and all government agencies. Although Mgovernment has emerged several years ago, these services are still in their early stage in developing countries in general, and in Saudi Arabia in particular. As any newly introduced concept into society, M-government is facing many difficulties in developing countries and not always accepted. There are many factors influencing the acceptance of M-government in developing countries, for instance the education level, the cost and complexity of use of technology, etc. Governments in developing countries, in general, and in Saudi Arabia in particular, are paying more attention towards the adoption of Mgovernment services by its nationals. This could be done, for example, by considering criteria that help making mobile services easily accepted by citizens, for example by implementing services that are user friendly and that are adequate to citizen needs. Our study is focusing on the adoption of M-government in Saudi Arabia. Our research question is: "What are the factors which influence the adoption of M-government in Saudi Arabia?" Answering this research question will enhance the knowledge in this field, by developing a conceptual model for citizens' adoption of M-government. The developed model integrates constructs from the Technology Acceptance Model (TAM), User's Satisfaction, Perceived Service Quality, Perceived Mobility and Trust. The developed model will provide more knowledge to the field of m-Government, either on the theoretical or practical sides. Theoretically, this study aims to determine the variables that are influencing the user intention to use m-Government services. This is made by exploring the applicability of TAM and other external variables derived from the related literature, such as perceived trust, perceived Service Quality, perceived Mobility and user's satisfaction. Practically, our study will help decision makers in M-government projects, in general, and mobile service providers, in particular, to successfully implement M-government services. This is made by providing a better understanding of the variables of the TAM and other external variables. To answer our research question, mixed research methods will be used (qualitative and quantitative methods). The relationships between these constructs form the basis for the research hypotheses which will be tested using a quantitative research approach. Specifically, a survey will be used for gathering data from a sample of Saudi citizens and statistical methods will be used for analysing the quantitative data generated from the primary research. Also, the qualitative data will be used to analyse and assist in explaining and refining the statistical results obtained from the quantitative results, specifically by investigating the participants' views
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Where do good query terms come from?
No full textThis paper describes a framework for investigating the quality of different query expansion approaches, and applies it in the HARD TREC experimental setting. The intuition behind our approach is that each topic has an optimal term-based representation, i.e. a set of terms that best describe it, and that the effectiveness of any other representation is correlated with the overlap that it has with the optimal representation. Indeed, we find that, for a wide number of candidate topic representations, obtained through various query-expansion approaches, there is a high correlation between standard effectiveness measures (R-P, P@10, MAP) and term overlap with what is estimated to be the optimal representation. An important conclusion of comparing different query expansion approaches is that machines are better than humans at doing statistical calculations and at
estimating which query terms are more likely to discriminate documents relevant for a given topic. This explains why, in the HARD track of TREC 2005, the overall conclusion was that interaction with the searcher and elicitation of additional
information could not over-perform automatic procedures for query improvement. However, the best results are obtained from hybrid approaches, in which human relevance judgments are used by algorithms for deriving terms representations. This result suggest that the best approach in improving retrieval performance is probably to focus on implicit relevance feedback and novel interaction models based on ostention or mediation, which have shown great potential
BERT Goes Off-Topic: Investigating the Domain Transfer Challenge using Genre Classification
Get PDFWhile performance of many text classification tasks has been recently
improved due to Pre-trained Language Models (PLMs), in this paper we show that
they still suffer from a performance gap when the underlying distribution of
topics changes. For example, a genre classifier trained on \textit{political}
topics often fails when tested on documents about \textit{sport} or
\textit{medicine}. In this work, we quantify this phenomenon empirically with a
large corpus and a large set of topics. Consequently, we verify that domain
transfer remains challenging both for classic PLMs, such as BERT, and for
modern large models, such as GPT-3. We also suggest and successfully test a
possible remedy: after augmenting the training dataset with
topically-controlled synthetic texts, the F1 score improves by up to 50\% for
some topics, nearing on-topic training results, while others show little to no
improvement. While our empirical results focus on genre classification, our
methodology is applicable to other classification tasks such as gender,
authorship, or sentiment classification. The code and data to replicate the
experiments are available at https://github.com/dminus1/genreComment: Published at EMNLP'202
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