Graph-Ontology Model of Cognitive-Similar Information Retrieval (on the Requirements Tracing Task Example)

2020 ◽  
pp. 218-224
Author(s):  
Nikolay V. Maksimov ◽  
Olga L. Golitsina ◽  
Kirill V. Monankov ◽  
Natalia A. Bal
Keyword(s):  
Information Retrieval ◽  
Ontology Model ◽  
Similar Information ◽  
Requirements Tracing

scholarly journals Concept-based Recommendation System for Finding Serendipity

2021 ◽  
Vol 12 (3) ◽  
pp. 2184-2190
Author(s):  
Kodai Tsukahara Et.al
Keyword(s):  
Information Retrieval ◽  
Recommendation System ◽  
Recommendation Systems ◽  
Research Purpose ◽  
Current Information ◽  
New Information ◽  
Similar Information ◽  
Information Recommendation ◽  
Filter Bubble ◽  
Output Information

Current information recommendation systems obtain users’ preferences from Web browsing histories and activities such as purchase of products, and efficiently provide the users with their preferable information. In such a case, however, the same or similar information is always recommended, which is called filter bubble and it decreases the users’ satisfaction to the systems. If information recommendation systems could provide users with something surprising and useful as output information, the user’s satisfaction to the systems would drastically increase. Therefore, “serendipity” is paid attention to in this research. In this paper, a new information recommendation system using a concept-based information retrieval is proposed to provide the users with serendipitous information. In this system, concepts which describe features or roles of items are input instead of the items themselves, and information which can meet the concepts are output as candidates of serendipitous information. The serendipitous information is extracted from the output information using the criteria which are the indexes of serendipity defined in this research. Through the evaluation experiment, it is revealed that the proposed system achieves the accuracy of 70% for the serendipitous information determination and the accuracy of 100% for the information retrieval, which are satisfactory for this research purpose.

Criminal Event Ontology Population and Enrichment using Patterns Recognition from Text

2019 ◽  
Vol 33 (11) ◽  
pp. 1940014 ◽  
Author(s):  
José A. Reyes-Ortiz
Keyword(s):  
Spanish Text ◽  
Social Networks ◽  
Pattern Recognition ◽  
Information Retrieval ◽  
Evaluation Process ◽  
Ontology Model ◽  
Important Variety ◽  
Violent Acts ◽  
Ontology Population ◽  
Event Ontology

Thousands of criminal events are reported in newspapers and social networks every day. They describe violent acts that include actors, places, times, causes and any information concerning them. Verbal and nominal phrases are used to characterize and expose criminal events, which employ an important variety of natural language structures in the newspapers. In addition, causes, times and spaces of criminal events, use linguistic phrases to represent them in text. All of them need to be extracted as a pattern recognition process in order to extract criminal events from text and the information that concerns them. The extracted events, as a knowledge base, are very useful for information retrieval tasks. Therefore, this paper presents an approach based on pattern recognition in order to extract criminal events from Spanish text, by populating and enriching an ontology model. Ontology population and enrichment involve the instantiation of criminal events and their cause relationships. An evaluation process is carried out with a set of manually tagged newspapers with categories of specific events, and shows promising results.

scholarly journals A FRAMEWORK FOR COMPARING REQUIREMENTS TRACING EXPERIMENTS

2005 ◽  
Vol 15 (05) ◽  
pp. 751-781 ◽  
Author(s):  
JANE HUFFMAN HAYES ◽  
ALEX DEKHTYAR
Keyword(s):  
Information Retrieval ◽  
Future Research ◽  
The Right ◽  
Requirements Tracing ◽  
Conference Papers

The building of traceability matrices by those other than the original developers is an arduous, error prone, prolonged, and labor intensive task. Thus, after-the-fact requirements tracing is a process where the right kind of automation can definitely assist an analyst. Recently, a number of researchers have studied the application of various methods, often based on information retrieval after-the-fact tracing. The studies are diverse enough to warrant a means for comparing them easily as well as for determining areas that require further investigation. To that end, we present here an experimental framework for evaluating requirements tracing and traceability studies. Common methods, metrics and measures are described. Recent experimental requirements tracing journal and conference papers are catalogued using the framework. We compare these studies and identify areas for future research. Finally, we provide suggestions on how the field of tracing and traceability research may move to a more mature level.

scholarly journals A Semantic Expansion Model for VGI Retrieval

2019 ◽  
Vol 8 (12) ◽  
pp. 589
Author(s):  
Sun ◽  
Xia ◽  
Li ◽  
Shen ◽  
Liu
Keyword(s):  
Information Retrieval ◽  
Spatial Information ◽  
Expansion Method ◽  
Geographic Information ◽  
Geographic Information Retrieval ◽  
Ontology Model ◽  
Representation Method ◽  
Semantic Expansion ◽  
Expansion Model ◽  
Relevant Experiment

OpenStreetMap (OSM) is a representative volunteered geographic information (VGI) project. However, there have been difficulties in retrieving spatial information from OSM. Ontology is an effective knowledge organization and representation method that is often used to enrich the search capabilities of search systems. This paper constructed an OSM ontology model with semantic property items. A query expansion method is also proposed based on the similarity of properties of the ontology model. Moreover, a relevant experiment is conducted using OSM data related to China. The experimental results demonstrate that the recall and precision of the proposed method reach 80% and 87% for geographic information retrieval, respectively. This study provides a method that can be used as a reference for subsequent research on spatial information retrieval.

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.

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