020 Bibliotheks- und Informationswissenschaft
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This assignment is about the development of a general strategic marketing plan for academic libraries in Germany and can be used as a guideline for libraries that want to develop concrete marketing strategies for several products and services. Two examples of marketing projects are at its end presented for linking theoretical approaches to practice. Finally the development of an own marketing strategy for “information literacy” builds the last part of the assignment.
A German university has developed a learning information system to improve information literacy among German students. An online tutorial based on this Lerninformationssystem has been developed. The structure of this learning information system is described, an online tutorial based on it is illustrated, and the different learning styles that it supports are indicated.
All of us are aware of the changes in the information field during the last years. We all see the paradigm shift coming up and have some idea how it will challenge our profession in the future. But how the road to excellence - in education of information specialists in the future - will look like? There are different models (new and old ones) for reorganising the structure of education: * Integration * Specialisation * Step-by step-model * Modul System * Network System / Combination model The paper will present the actual level of discussion on building up a new curriculum at the Department of Information and Communication (IK) at the FH Hannover. Based on the mission statement of the department »Education of information professionals is a part of the dynamic evolution of knowledge society« the direction of change and the main goals will be presented. The different reorganisation models will be explained with its objectives, opportunities and forms of implementation. Some examples will show the ideas and tools for a first draft of a reconstruction plan to become fit for the future. This talk has been held at the German-Dutch University Conference »Information Specialists for the 21st Century« at the Fachhochschule Hannover - University of Applied Sciences, Department of Information and Communication, October 14 -15, 1999 in Hannover, Germany.
On April, 23rd 2007 a series of postings started on Infobib.de, where guest authors from all over the world introduced the library and library related blogs of their own country. This book is a collection of 30 revised LibWorld articles, accompanied by a foreword by Walt Crawford. Included are articles about the blogosphere of: Argentina, Australia, Austria, Belarus, Belgium, Brazil, Canada, Denmark, Finland, France, Greece, Hungary, Iran, Italy, Japan, Latvia, Malawi, Netherlands, New Zealand, Norway, Peru, Puerto Rico, Russia, Singapore, Spain, Sweden, Switzerland, Trinidad & Tobago, USA.
Primary data is an important source ofinformation for Competitive Intelligence. Traditionally, it has been collected from interviews with stakeholders, talks at conferences and other means of direct interpersonal communication. The role of the Internet in the data collection – if it was used at all – was that of a provider of supplementary secondary data. Here, this approach is challenged and, using three examples of Social Media, it is shown that the Internet can and does provide valuable primary information to the Competitive Intelligence professional. Accordingly, a case is made for a shift of focus in the data collection process.
Automatic classification of scientific records using the German Subject Heading Authority File (SWD)
(2012)
The following paper deals with an automatic text classification method which does not require training documents. For this method the German Subject Heading Authority File (SWD), provided by the linked data service of the German National Library is used. Recently the SWD was enriched with notations of the Dewey Decimal Classification (DDC). In consequence it became possible to utilize the subject headings as textual representations for the notations of the DDC. Basically, we we derive the classification of a text from the classification of the words in the text given by the thesaurus. The method was tested by classifying 3826 OAI-Records from 7 different repositories. Mean reciprocal rank and recall were chosen as evaluation measure. Direct comparison to a machine learning method has shown that this method is definitely competitive. Thus we can conclude that the enriched version of the SWD provides high quality information with a broad coverage for classification of German scientific articles.
Distributional semantics tries to characterize the meaning of words by the contexts in which they occur. Similarity of words hence can be derived from the similarity of contexts. Contexts of a word are usually vectors of words appearing near to that word in a corpus. It was observed in previous research that similarity measures for the context vectors of two words depend on the frequency of these words. In the present paper we investigate this dependency in more detail for one similarity measure, the Jensen-Shannon divergence. We give an empirical model of this dependency and propose the deviation of the observed Jensen-Shannon divergence from the divergence expected on the basis of the frequencies of the words as an alternative similarity measure. We show that this new similarity measure is superior to both the Jensen-Shannon divergence and the cosine similarity in a task, in which pairs of words, taken from Wordnet, have to be classified as being synonyms or not.
Regional Innovation Systems describe the relations between actors, structures and infrastructures in a region in order to stimulate innovation and regional development. For these systems the collection and organization of information is crucial. In the present paper we investigate the possibilities to extract information from websites of companies. First we describe regional innovation systems and the information types that are necessary to create them. Then we discuss the possibilities of text mining and keyword extraction techniques to extract this information from company websites. Finally, we describe a small scale experiment in which keywords related to economic sectors and commodities are extracted from the websites of over 200 companies. This experiment shows what the main challenges are for information extraction from websites for regional innovation systems.
We compare the effect of different segmentation strategies for passage retrieval of user generated internet video. We consider retrieval of passages for rather abstract and complex queries that go beyond finding a certain object or constellation of objects in the visual channel. Hence the retrieval methods have to rely heavily on the recognized speech. Passage retrieval has mainly been studied to improve document retrieval and to enable question answering. In these domains best results were obtained using passages defined by the paragraph structure of the source documents or by using arbitrary overlapping passages. For the retrieval of relevant passages in a video no author defined paragraph structure is available. We compare retrieval results from 5 different types of segments: segments defined by shot boundaries, prosodic segments, fixed length segments, a sliding window and semantically coherent segments based on speech transcripts. We evaluated the methods on the corpus of the MediaEval 2011 Rich Speech Retrieval task. Our main conclusions are (1) that fixed length and coherent segments are clearly superior to segments based on speaker turns or shot boundaries; (2) that the retrieval results highly depend on the right choice for the segment length; and (3) that results using the segmentation into semantically coherent parts depend much less on the segment length. Especially, the quality of fixed length and sliding window segmentation drops fast when the segment length increases, while quality of the semantically coherent segments is much more stable. Thus, if coherent segments are defined, longer segments can be used and consequently fewer segments have to be considered at retrieval time.
Regional knowledge map is a tool recently demanded by some actors in an institutional level to help regional policy and innovation in a territory. Besides, knowledge maps facilitate the interaction between the actors of a territory and the collective learning. This paper reports the work in progress of a research project which objective is to define a methodology to efficiently design territorial knowledge maps, by extracting information of big volumes of data contained in diverse sources of information related to a region. Knowledge maps facilitate management of the intellectual capital in organisations. This paper investigates the value to apply this tool to a territorial region to manage the structures, infrastructures and the resources to enable regional innovation and regional development. Their design involves the identification of information sources that are required to find which knowledge is located in a territory, which actors are involved in innovation, and which is the context to develop this innovation (structures, infrastructures, resources and social capital). This paper summarizes the theoretical background and framework for the design of a methodology for the construction of knowledge maps, and gives an overview of the main challenges for the design of regional knowledge maps.