Diese Datenbank enthält über 40.000 Dokumente zu Themen aus den Bereichen Formalerschließung – Inhaltserschließung – Information Retrieval.
© 2015 W. Gödert, TH Köln, Institut für Informationswissenschaft / Powered by litecat, BIS Oldenburg (Stand: 16. Dezember 2019)
1Thelwall, M.: Web indicators for research evaluation : a practical guide.
San Rafael, CA : Morgan & Claypool Publishers, 2016. 170 S.
(Synthesis lectures on information concepts, retrieval, and services; 52)
Abstract: In recent years there has been an increasing demand for research evaluation within universities and other research-based organisations. In parallel, there has been an increasing recognition that traditional citation-based indicators are not able to reflect the societal impacts of research and are slow to appear. This has led to the creation of new indicators for different types of research impact as well as timelier indicators, mainly derived from the Web. These indicators have been called altmetrics, webometrics or just web metrics. This book describes and evaluates a range of web indicators for aspects of societal or scholarly impact, discusses the theory and practice of using and evaluating web indicators for research assessment and outlines practical strategies for obtaining many web indicators. In addition to describing impact indicators for traditional scholarly outputs, such as journal articles and monographs, it also covers indicators for videos, datasets, software and other non-standard scholarly outputs. The book describes strategies to analyse web indicators for individual publications as well as to compare the impacts of groups of publications. The practical part of the book includes descriptions of how to use the free software Webometric Analyst to gather and analyse web data. This book is written for information science undergraduate and Master?s students that are learning about alternative indicators or scientometrics as well as Ph.D. students and other researchers and practitioners using indicators to help assess research impact or to study scholarly communication.
Anmerkung: Rez. in: JASIST 69(2018) no.3, S.498-499 (Isidro F. Aguillo).
LCSH: Electronic books
RSWK: Altmetrische Daten
RVK: AK 28100
2Tonkin, E.L. ; Tourte, G.J.L.: Working with text. tools, techniques and approaches for text mining.
Cambridge (MA) : Chandos Publisher, 2016. xiii, 330 S.
(Chandos Information Professional Series)
Abstract: What is text mining, and how can it be used? What relevance do these methods have to everyday work in information science and the digital humanities? How does one develop competences in text mining? Working with Text provides a series of cross-disciplinary perspectives on text mining and its applications. As text mining raises legal and ethical issues, the legal background of text mining and the responsibilities of the engineer are discussed in this book. Chapters provide an introduction to the use of the popular GATE text mining package with data drawn from social media, the use of text mining to support semantic search, the development of an authority system to support content tagging, and recent techniques in automatic language evaluation. Focused studies describe text mining on historical texts, automated indexing using constrained vocabularies, and the use of natural language processing to explore the climate science literature. Interviews are included that offer a glimpse into the real-life experience of working within commercial and academic text mining.
Anmerkung: Rez. in: JASIST 69(2018) no.1, S.181-184 (Jacques Savoy).
Themenfeld: Data Mining
LCSH: Data mining
RSWK: Text Mining / Aufsatzsammlung
RVK: ST 680
3Stuart, D.: Web metrics for library and information professionals.
London : Facet Publ., 2014. VII, 199 S.
Abstract: This is a practical guide to using web metrics to measure impact and demonstrate value. The web provides an opportunity to collect a host of different metrics, from those associated with social media accounts and websites to more traditional research outputs. This book is a clear guide for library and information professionals as to what web metrics are available and how to assess and use them to make informed decisions and demonstrate value. As individuals and organizations increasingly use the web in addition to traditional publishing avenues and formats, this book provides the tools to unlock web metrics and evaluate the impact of this content. The key topics covered include: bibliometrics, webometrics and web metrics; data collection tools; evaluating impact on the web; evaluating social media impact; investigating relationships between actors; exploring traditional publications in a new environment; web metrics and the web of data; the future of web metrics and the library and information professional. The book will provide a practical introduction to web metrics for a wide range of library and information professionals, from the bibliometrician wanting to demonstrate the wider impact of a researcher's work than can be demonstrated through traditional citations databases, to the reference librarian wanting to measure how successfully they are engaging with their users on Twitter. It will be a valuable tool for anyone who wants to not only understand the impact of content, but demonstrate this impact to others within the organization and beyond.
Inhalt: 1. Introduction. MetricsIndicators -- Web metrics and Ranganathan's laws of library science -- Web metrics for the library and information professional -- The aim of this book -- The structure of the rest of this book -- 2. Bibliometrics, webometrics and web metrics. Web metrics -- Information science metrics -- Web analytics -- Relational and evaluative metrics -- Evaluative web metrics -- Relational web metrics -- Validating the results -- 3. Data collection tools. The anatomy of a URL, web links and the structure of the web -- Search engines 1.0 -- Web crawlers -- Search engines 2.0 -- Post search engine 2.0: fragmentation -- 4. Evaluating impact on the web. Websites -- Blogs -- Wikis -- Internal metrics -- External metrics -- A systematic approach to content analysis -- 5. Evaluating social media impact. Aspects of social network sites -- Typology of social network sites -- Research and tools for specific sites and services -- Other social network sites -- URL shorteners: web analytic links on any site -- General social media impact -- Sentiment analysis -- 6. Investigating relationships between actors. Social network analysis methods -- Sources for relational network analysis -- 7. Exploring traditional publications in a new environment. More bibliographic items -- Full text analysis -- Greater context -- 8. Web metrics and the web of data. The web of data -- Building the semantic web -- Implications of the web of data for web metrics -- Investigating the web of data today -- SPARQL -- Sindice -- LDSpider: an RDF web crawler -- 9. The future of web metrics and the library and information professional. How far we have come -- The future of web metrics -- The future of the library and information professional and web metrics.
Anmerkung: Rez. in: JASIST 66(2015) no.11, S.2392-2395 (Enrique Orduña-Malea)
Themenfeld: Informetrie ; Internet
LCSH: Resource description & access ; Webometrics ; Data mining ; Library science
RSWK: Bibliothek / World Wide Web / World Wide Web 2.0 / Analyse / Statistik ; Bibliometrie / Semantic Web / Soziale Software ; Internet / Bibliometrie / Einführung
BK: 54.84 Webmanagement ; 06.00 Information und Dokumentation: Allgemeines
DDC: 025.042 ; 006.312
GHBS: AZC (E)
RVK: AN 96300 ; AN 96400
4Liu, B.: Web data mining : exploring hyperlinks, contents, and usage data.2nd ed.
Heidelberg : Springer, 2011. XX, 622 S.
(Data-centric systems and applications)
Abstract: Web mining aims to discover useful information and knowledge from the Web hyperlink structure, page contents, and usage data. Although Web mining uses many conventional data mining techniques, it is not purely an application of traditional data mining due to the semistructured and unstructured nature of the Web data and its heterogeneity. It has also developed many of its own algorithms and techniques. Liu has written a comprehensive text on Web data mining. Key topics of structure mining, content mining, and usage mining are covered both in breadth and in depth. His book brings together all the essential concepts and algorithms from related areas such as data mining, machine learning, and text processing to form an authoritative and coherent text. The book offers a rich blend of theory and practice, addressing seminal research ideas, as well as examining the technology from a practical point of view. It is suitable for students, researchers and practitioners interested in Web mining both as a learning text and a reference book. Lecturers can readily use it for classes on data mining, Web mining, and Web search. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.
Inhalt: Inhalt: 1. Introduction 2. Association Rules and Sequential Patterns 3. Supervised Learning 4. Unsupervised Learning 5. Partially Supervised Learning 6. Information Retrieval and Web Search 7. Social Network Analysis 8. Web Crawling 9. Structured Data Extraction: Wrapper Generation 10. Information Integration
Anmerkung: Elektronische Ausgabe unter: http://springer.r.delivery.net/r/r?2.1.Ee.2Tp.1gd0L5.C3WE8i..N.WdtE.3uq2.bW89MQ%5f%5fCXPUFOH0.
Themenfeld: Data Mining
RSWK: World Wide Web / Data Mining
BK: 54.72 ; 06.74 ; 06.70 ; 54.32
DDC: 006.312 / DDC22ger ; 005.7402854678 / DDC22ger ; 005.72 / DDC22ger
GHBS: TZG (FH K) ; TWX (FH GE)
RVK: ST 530
5Berry, M.W. (Hrsg.): Survey of text mining : clustering, classification, and retrieval.
New York, NY : Springer, 2004. XVII, 244 S.
Abstract: Extracting content from text continues to be an important research problem for information processing and management. Approaches to capture the semantics of text-based document collections may be based on Bayesian models, probability theory, vector space models, statistical models, or even graph theory. As the volume of digitized textual media continues to grow, so does the need for designing robust, scalable indexing and search strategies (software) to meet a variety of user needs. Knowledge extraction or creation from text requires systematic yet reliable processing that can be codified and adapted for changing needs and environments. This book will draw upon experts in both academia and industry to recommend practical approaches to the purification, indexing, and mining of textual information. It will address document identification, clustering and categorizing documents, cleaning text, and visualizing semantic models of text.
Themenfeld: Data Mining
LCSH: Data mining ; Information retrieval ; Data mining / Congresses (GBV) ; Cluster analysis / Congresses (GBV) ; Discriminant analysis / Congresses (GBV)
RSWK: Text Mining / Aufsatzsammlung
BK: 54.72 / Künstliche Intelligenz ; 06.74 / Informationssysteme
DDC: 005.741 ; 006.3
RVK: ST 270 Informatik / Monographien / Software und -entwicklung / Datenbanken, Datenbanksysteme, Data base management, Informationssysteme ; ST 302 Informatik / Monographien / Künstliche Intelligenz / Expertensysteme; Wissensbasierte Systeme
6Kantardzic, M.: Data mining : concepts, models, methods, and algorithms.
Hoboken, NJ : Wiley-Interscience, 2003. XII, 345 S.
Abstract: This book offers a comprehensive introduction to the exploding field of data mining. We are surrounded by data, numerical and otherwise, which must be analyzed and processed to convert it into information that informs, instructs, answers, or otherwise aids understanding and decision-making. Due to the ever-increasing complexity and size of today's data sets, a new term, data mining, was created to describe the indirect, automatic data analysis techniques that utilize more complex and sophisticated tools than those which analysts used in the past to do mere data analysis. "Data Mining: Concepts, Models, Methods, and Algorithms" discusses data mining principles and then describes representative state-of-the-art methods and algorithms originating from different disciplines such as statistics, machine learning, neural networks, fuzzy logic, and evolutionary computation. Detailed algorithms are provided with necessary explanations and illustrative examples. This text offers guidance: how and when to use a particular software tool (with their companion data sets) from among the hundreds offered when faced with a data set to mine. This allows analysts to create and perform their own data mining experiments using their knowledge of the methodologies and techniques provided. This book emphasizes the selection of appropriate methodologies and data analysis software, as well as parameter tuning. These critically important, qualitative decisions can only be made with the deeper understanding of parameter meaning and its role in the technique that is offered here. Data mining is an exploding field and this book offers much-needed guidance to selecting among the numerous analysis programs that are available.
Themenfeld: Data Mining
LCSH: Data mining
RSWK: Data Mining / Lehrbuch
BK: 06.74 Informationssysteme
DDC: 006.3/12 / dc22
GHBS: TWX (E) ; PZY (FH K)
LCC: QA76.9.D343K36 2003
RVK: ST 270 ; ST 530