Information retrieval, information structure, and information agents

1997 ◽  
pp. 145-182
Author(s):  
Daniela Rus ◽  
Devika Subramanian
Keyword(s):  
Information Retrieval ◽  
Information Structure ◽  
Information Agents

Literature Review in Computational Linguistics Issues in the Developing Field of Consumer Informatics

2011 ◽  
pp. 226-232
Author(s):  
Ki Jung Lee
Keyword(s):  
Information Retrieval ◽  
Computational Linguistics ◽  
Information Structure ◽  
Information Needs ◽  
Retrieval System ◽  
Medical Information ◽  
Information Retrieval System ◽  
Search Results ◽  
Medical Information Retrieval ◽  
On Line

With the increased use of Internet, a large number of consumers first consult on line resources for their healthcare decisions. The problem of the existing information structure primarily lies in the fact that the vocabulary used in consumer queries is intrinsically different from the vocabulary represented in medical literature. Consequently, the medical information retrieval often provides poor search results. Since consumers make medical decisions based on the search results, building an effective information retrieval system becomes an essential issue. By reviewing the foundational concepts and application components of medical information retrieval, this paper will contribute to a body of research that seeks appropriate answers to a question like “How can we design a medical information retrieval system that can satisfy consumer’s information needs?”

Literature Review in Computational Linguistics Issues in the Developing Field of Consumer Informatics

2010 ◽  
pp. 758-765 ◽  
Author(s):  
Ki Jung Lee
Keyword(s):  
Information Retrieval ◽  
Computational Linguistics ◽  
Information Structure ◽  
Information Needs ◽  
Retrieval System ◽  
Medical Information ◽  
Information Retrieval System ◽  
Search Results ◽  
Medical Information Retrieval ◽  
On Line

With the increased use of Internet, a large number of consumers first consult on line resources for their healthcare decisions. The problem of the existing information structure primarily lies in the fact that the vocabulary used in consumer queries is intrinsically different from the vocabulary represented in medical literature. Consequently, the medical information retrieval often provides poor search results. Since consumers make medical decisions based on the search results, building an effective information retrieval system becomes an essential issue. By reviewing the foundational concepts and application components of medical information retrieval, this paper will contribute to a body of research that seeks appropriate answers to a question like “How can we design a medical information retrieval system that can satisfy consumer’s information needs?”

Theme

2017 ◽  
Author(s):  
Eva Hajičová
Keyword(s):  
Information Retrieval ◽  
Information Structure ◽  
Point Of View ◽  
Semantic Relations ◽  
Surface Shape ◽  
Sentence Structure ◽  
Generative Theory ◽  
Thematic Relations ◽  
Sentence Boundary ◽  
Morphosyntactic Analysis

In the linguistic literature, the term theme has several interpretations, one of which relates to discourse analysis and two others to sentence structure. In a more general (or global) sense, one may speak about the theme or topic (or topics) of a text (or discourse), that is, to analyze relations going beyond the sentence boundary and try to identify some characteristic subject(s) for the text (discourse) as a whole. This analysis is mostly a matter of the domain of information retrieval and only partially takes into account linguistically based considerations. The main linguistically based usage of the term theme concerns relations within the sentence. Theme is understood to be one of the (syntactico-) semantic relations and is used as the label of one of the arguments of the verb; the whole network of these relations is called thematic relations or roles (or, in the terminology of Chomskyan generative theory, theta roles and theta grids). Alternatively, from the point of view of the communicative function of the language reflected in the information structure of the sentence, the theme (or topic) of a sentence is distinguished from the rest of it (rheme, or focus, as the case may be) and attention is paid to the semantic consequences of the dichotomy (especially in relation to presuppositions and negation) and its realization (morphological, syntactic, prosodic) in the surface shape of the sentence. In some approaches to morphosyntactic analysis the term theme is also used referring to the part of the word to which inflections are added, especially composed of the root and an added vowel.

SEQUENTIAL PATTERN MINING AND NONMONOTONIC REASONING FOR INTELLIGENT INFORMATION AGENTS

2007 ◽  
Vol 21 (04) ◽  
pp. 773-789 ◽  
Author(s):  
RAYMOND Y. K. LAU ◽  
YUEFENG LI ◽  
SHENG-TANG WU ◽  
XUJUAN ZHOU
Keyword(s):  
Data Mining ◽  
Information Retrieval ◽  
Belief Revision ◽  
Pattern Mining ◽  
Sequential Pattern Mining ◽  
Sequential Pattern ◽  
Sequential Data ◽  
Contextual Knowledge ◽  
Information Agents ◽  
Intelligent Information

With the explosive growth of information available on the Internet, more effective data mining and data reasoning mechanism is required to process the sheer volume of information. Belief revision logic offers the expressive power to represent information retrieval contexts, and it also provides a sound inference mechanism to model the nonmonotonicity arising in changing retrieval contexts. Contextual knowledge for information retrieval can be extracted via efficient sequential pattern mining. We present a pattern taxonomy extraction model which efficiently performs the task of discovering descriptive frequent sequential patterns by pruning the noisy associations. This paper illustrates a novel approach of integrating the sequential data mining method into the belief revision based adaptive information agents to improve the agents' learning autonomy and prediction power. Initial experiments show that our belief revision logic and sequential pattern mining based intelligent information agents outperform the vector space model based information agents. Our work opens the door to the development of next generation of intelligent information agents to alleviate the information overload problem.

Demonstration of the Use of Tape-Recorded Information from a High Vacuum Electron Microscope

1969 ◽  
Vol 27 ◽  
pp. 218-219
Author(s):  
Richard E. Hartman ◽  
Roberta S. Hartman ◽  
Peter L. Ramos
Keyword(s):  
Information Retrieval ◽  
Electron Microscope ◽  
Magnetic Tape ◽  
High Vacuum ◽  
Data Retrieval ◽  
Electronic Information ◽  
Electronic Data ◽  
Subsequent Processing ◽  
Continuous Record

We have long felt that some form of electronic information retrieval would be more desirable than conventional photographic methods in a high vacuum electron microscope for various reasons. The most obvious of these is the fact that with electronic data retrieval the major source of gas load is removed from the instrument. An equally important reason is that if any subsequent analysis of the data is to be made, a continuous record on magnetic tape gives a much larger quantity of data and gives it in a form far more satisfactory for subsequent processing.

Stain contamination and embedding in electron microscopy

1986 ◽  
Vol 44 ◽  
pp. 50-53
Author(s):  
Hilton H. Mollenhauer
Keyword(s):  
Electron Microscopy ◽  
Information Retrieval ◽  
Epoxy Resins ◽  
Image Contrast ◽  
Sample Preservation ◽  
Factors Associated ◽  
Amount Of Information ◽  
Electron Microscopical ◽  
Contrast Information

Many factors (e.g., resolution of microscope, type of tissue, and preparation of sample) affect electron microscopical images and alter the amount of information that can be retrieved from a specimen. Of interest in this report are those factors associated with the evaluation of epoxy embedded tissues. In this context, informational retrieval is dependant, in part, on the ability to “see” sample detail (e.g., contrast) and, in part, on tue quality of sample preservation. Two aspects of this problem will be discussed: 1) epoxy resins and their effect on image contrast, information retrieval, and sample preservation; and 2) the interaction between some stains commonly used for enhancing contrast and information retrieval.

Information and Dose in the Scanning Transmission Ion Microscope

1980 ◽  
Vol 38 ◽  
pp. 232-233
Author(s):  
Fox T. R. ◽  
R. Levi-Setti
Keyword(s):  
Information Retrieval ◽  
Electron Microscope ◽  
Elastic Scattering ◽  
Energy Loss ◽  
Cross Sections ◽  
Previous Analysis ◽  
Single Scattering ◽  
Screening Length ◽  
Relative Damage ◽  
Scanning Transmission

At an earlier meeting [1], we discussed information retrieval in the scanning transmission ion microscope (STIM) compared with the electron microscope at the same energy. We treated elastic scattering contrast, using total elastic cross sections; relative damage was estimated from energy loss data. This treatment is valid for “thin” specimens, where the incident particles suffer only single scattering. Since proton cross sections exceed electron cross sections, a given specimen (e.g., 1 μg/cm2 of carbon at 25 keV) may be thin for electrons but “thick” for protons. Therefore, we now extend our previous analysis to include multiple scattering. Our proton results are based on the calculations of Sigmund and Winterbon [2], for 25 keV protons on carbon, using a Thomas-Fermi screened potential with a screening length of 0.0226 nm. The electron results are from Crewe and Groves [3] at 30 keV.

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