Forskningsfronten inom informationsvetenskap - BADA

1. FF: Walters GD TI: Measuring the utility of journals in the crime-psychology field: Beyond the
impact factor ÄO: Saknas
2. FF: Knothe G TI: Comparative citation analysis of duplicate or highly related publications ÄO:
ENANTIOSELECTIVE TOTAL-SYNTHESIS; 1ST TOTAL-SYNTHESIS; DOUBLE-BOND;
STEREOCONTROLLED SYNTHESIS; MASS-SPECTROMETRY; PINENE PATH; TAXOL; ACID;
POSITION; IMPACT
3. FF: Wang JX; Guan JC TI: The analysis and evaluation of knowledge efficiency in research groups
ÄO: DATA ENVELOPMENT ANALYSIS; IMPACT; SCIENCE; PERFORMANCE;
MANAGEMENT; JOURNALS; CREATION; MODEL; DEA
4. FF: Sombatsompop N; Markpin T TI: Making an equality of ISI impact factors for different subject
fields ÄO: Saknas
5. FF: Clyde LA TI: Evaluating the quality of research publications: A pilot study of school
librarianship ÄO: LIBRARY INFORMATION-SCIENCE; JOURNAL LITERATURE; IMPACT
FACTOR; PROFESSIONAL JOURNALS; PERCEIVED PRESTIGE; CITATION
6. FF: Vinkler P TI: Characterization of the impact of sets of scientific papers: The Garfield (Impact)
Factor ÄO: INDICATORS; CITATION; SCIENTOMETRICS; MODEL
Detta forskningstema har vi valt att kalla ”Utvärdering av vetenskapliga tidskrifter” -
något som kan göras på olika sätt. De flesta av artiklarna handlar om citeringsanalys. I
tre av artiklarna tar man upp Impact factor 14 , som mäter vilken betydelse ett objekt (till
exempel tidskrifter) har.
Kluster 8. Forskningstema “Textkategorisering”
1. FF: Koppel M; Akiva N; Dagan I TI: Feature instability as a criterion for selecting potential style
markers ÄO: TEXT CATEGORIZATION
2. FF: Zheng R; Li JX; Chen HC; Huang Z TI: A framework for authorship identification of Online
messages: Writing-style features and classification techniques ÄO: SUPPORT VECTOR MACHINES;
NEURAL-NETWORKS; STYLOMETRIC ANALYSIS; ATTRIBUTION; FEDERALIST; DESIGN
3. FF: Sun A; Lim EP TI: Web unit-based mining of homepage relationships ÄO: saknas
4. FF: Yoon Y; Lee C; Lee GG TI: An effective procedure for constructing a hierarchical text
classification system ÄO: CATEGORIZATION
5. FF: Debole F; Sebastiani F TI: An analysis of the relative hardness of Reuters-21578 subsets ÄO:
AUTOMATED TEXT CATEGORIZATION
6. FF: Diaz I; Ranilla J; Montanes E; Fernandez J; Combarro EF TI: Improving performance of text
categorization by combining filtering and support vector machines
7. FF: Melucci M TI: Making digital libraries effective: Automatic generation of links for similarity
search across hyper-textbooks ÄO: DESIGN; CONSTRUCTION; TOOL; WEB
8. FF: Frank E; Paynter GW TI: Predicting library of Library of Congress Classifications from congress
subject headings
Med forskningstema “Textkategorisering” menar vi här analyser av text i syfte att kunna
dela in antingen textens författare eller textens olika byggstenar i kategorier. Artikel ett
handlar till exempel om att kunna identifiera och utarbeta synonymer i en text. I artikel
14 Se kapitelavsnitt 3.2
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