The purpose of this research is to simulate the manual process of assigning descriptors to magazine articles by machine, to investigate how successful automated assignment of descriptors to a heterogeneous text collection is when a text classifier is trained based upon a small set of manually classified example texts, and to test performance of…

Report on exploratory research which investigated image attributes in a series of describing tasks. Results suggest that access to a wide range of attributes is needed to address all facets of interest and that certain classes of attributes may appear more frequently (literal objects, human form and associated attributes, color, and location).…

This study examine 60 corporate Web sites to see if they provided support for automatic indexing, particularly use of the robots.txt and Meta tags for keywords and description. Discusses the use of Java and cookies and suggests that an increase in indexing aids would improve overall index coverage of the Web. (Author/LRW)

Discusses the inclusion of contextual information in indexing and retrieval systems to improve results and the ability to carry out text analysis by means of linguistic knowledge. Presents research that investigated whether discourse variables have an impact on information and retrieval and classification algorithms. (Author/LRW)

This study proposes a probabilistic model for automatically extracting English noun phrases for indexing or information retrieval. The technique is based on a Markov model, whose initial parameters are estimated by a phrase lookup program with a phrase dictionary, then optimized by a set of maximum entropy parameters. (Author/LRW)

Highlights semantic links and shows how the semantic content of hypertext links can be used for information retrieval. Discussion includes indexing and retrieval algorithms that exploit link content and node content; retrieval strategies exploiting semantic links, including conventional retrieval and constrained spreading activation techniques;…

Discussion of MEDLINE document indexing focuses on a study that assessed the use of free text, Medical Subject Headings (MeSH), and a variety of combination retrieval strategies. Prior research involving free text and controlled vocabularies is reviewed, and results of the study indicate that MeSH does have an important role in text retrieval.…

Describes the VISION (video indexing for searching over networks) digital video library system which was developed at the University of Kansas as a testbed for evaluating automatic and comprehensive mechanisms for library creation and content-based search and retrieval of video over local and wide area networks. Discusses experimental results.…

The Latent Semantic Indexing and MatchPlus systems examine similar contexts in which words appear and create representational models that capture the similarity of meaning of terms and then use the representation for retrieval. Text Retrieval Conference experiments using these systems demonstrate the computational feasibility of using…

Suggests an alternative document representation method based on "exemplary documents," those that describe or exhibit the intellectual structure of a particular field of interest. Exemplary documents provide both an indexing vocabulary for that area and a narrative context in which the indexing terms have a clearer meaning. It is much…

Investigated undergraduate art history majors' image retrieval tasks and image query modes. Discusses gender differences; prior information retrieval experience; significant differences between the number of search terms users planned to use and the number they actually used; and implications for image indexing tools, image retrieval system…

Explores the indirect method of locating for indexing the likely explicit and implicit captions of photographs, using multimodal clues including the specific words used, syntax, surrounding layout of the Web page, and general appearance of the associated image. The MARIE-3 system thus avoids full image processing and full natural-language…