scholarly journals INTELLIGENT DATA MODEL FOR ARABIC MORPHOLOGY: MORPHOSCRIPT LANGUAGE

2021 ◽  
Vol 56 (5) ◽  
pp. 442-456
Author(s):  
Sonia Abdelmoumni ◽  
Noureddine Chenfour
Keyword(s):  
Natural Language ◽  
Data Model ◽  
Morphological Analysis ◽  
Object Oriented ◽  
Morphological Knowledge ◽  
Analysis Process ◽  
Indexing System ◽  
Adequate Representation ◽  
Arabic Morphology ◽  
Adequate Data

This paper aims to propose a specific formalism for Arabic morphology modeling that is too complex to model exhaustively with classical approaches. Therefore, it was necessary to find out an adequate representation of formalism. We designed, thus, a declarative, object-oriented language, referenced to us: MorphoScript, which allowed us to represent the complete morphological knowledge that we could identify optimally. The study that we are presenting here aims to propose an adequate data model of natural language morphological components and composition rules. We will thus present the basic elements and the theoretical and technical foundations of a language reproducing and assisting a morphological analysis process and the principles that guided the conception of this data model fully based on class concepts. Therefore, it is an object-oriented language using inheritance as basic support to define the morphological links between the different morphological classes. We have also used aggregation concepts and an annotation indexing system allowing the morphological designer a better representation of morphological knowledge.

Building back-of-the-book indexes

Terminology ◽  
2005 ◽  
Vol 11 (1) ◽  
pp. 199-224 ◽  
Author(s):  
Adeline Nazarenko ◽  
Touria Aït El Mekki
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Indexing System

This paper presents an original natural language processing (NLP) approach for building of back-of-the-book indexes. Our indexing system, IndDoc, exploits some terminological tools and automatically builds an index draft of the analysis of the document text. The indexer then has to validate that index draft through a dedicated interface. This approach has been tested on several documents with promising results. Relying on our experience in developing and testing the IndDoc indexing system, we aim at assessing the contribution of terminological analysis as well as the level of maturity that computational terminology has reached in the indexing perspective.

ODM: An object oriented data model

1989 ◽  
Vol 7 (1) ◽  
pp. 3-35
Author(s):  
Mojtaba Mozaffari ◽  
Yuzuru Tanaka
Keyword(s):  
Data Model ◽  
Object Oriented

Study of the Spatio-Temporal Data Model in Sea Battlefield

2012 ◽  
Vol 246-247 ◽  
pp. 744-748
Author(s):  
Yue Lin Sun ◽  
Lei Bao ◽  
Yi Hang Peng
Keyword(s):  
Data Model ◽  
Object Oriented ◽  
Space Time ◽  
Comprehensive Analysis ◽  
Temporal Data ◽  
Data Types ◽  
Spatio Temporal ◽  
The Right ◽  
Effective Analysis

An effective analysis of the battlefield situation and spatio-temporal data model in a sea battlefield has great significance for the commander to perceive the battlefield situation and to make the right decisions. Based on the existing spatio-temporal data model, the present paper gives a comprehensive analysis of the characteristics of sea battlefield data, and chooses the object-oriented spatio-temporal data model to modify it; at the same time this paper introduces sea battlefield space-time algebra system to define various data types formally, which lays the foundation for the establishment of the sea battlefield spatio-temporal data model.

Integrated 3D Spatial Data Model of Object-Oriented Digital Landslide

2012 ◽  
Vol 204-208 ◽  
pp. 4872-4877
Author(s):  
Da Xi Ma ◽  
Xiao Hong Liu ◽  
Li Wei Ma
Keyword(s):  
Spatial Data ◽  
Data Model ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Data Modeling ◽  
Object Oriented ◽  
Landslide Modeling ◽  
Space Data ◽  
Spatial Data Model ◽  
Three Dimensional Space

By analyzing the attributes of three-dimensional space data model, the integrated 3D spatial data adopts object-oriented method for digital landslide modeling. It achieves spatial data modeling for landslide geological entity. An experimental case is given to indicate the feasibility of this approach for spatial data modeling.

Data Base Requirements for Concurrent Design Systems

1991 ◽  
Author(s):  
Ranko Vujosevic ◽  
Andrew Kusiak
Keyword(s):  
Data Base ◽  
Data Model ◽  
Object Oriented ◽  
Concurrent Design ◽  
Complex Objects ◽  
Maintenance System ◽  
Design And Manufacturing ◽  
Design Systems ◽  
Truth Maintenance ◽  
Definition Of

Abstract The data base requirements for concurrent design systems are discussed. An object-oriented data base, which allows for definition of complex objects, specification of relationships between objects, and modular expandability without affecting the existing information is defined. The data base is developed based on the object-oriented data model implemented in Smalltalk-80. An assumption-based truth maintenance system for maintaining the dependency relationships between design and manufacturing information is described.

Researches on the Object-Oriented Model of Distributed Image Database

2014 ◽  
Vol 543-547 ◽  
pp. 2184-2187
Author(s):  
Ping Zhang Gou ◽  
Yong Zhong Tang
Keyword(s):  
Comparative Analysis ◽  
Data Model ◽  
Object Oriented ◽  
Image Data ◽  
Image Database ◽  
Management Modes

Combined with the characteristics of the image data, this study contrasted four kinds of data model. Then it analyzed the three kinds of realization methods of image database, comparative analysis of management modes of the distributed image database finally.

scholarly journals Implementation of a Cohort Retrieval System for Clinical Data Repositories Using the Observational Medical Outcomes Partnership Common Data Model: Proof-of-Concept System Validation (Preprint)

2019 ◽  
Author(s):  
Sijia Liu ◽  
Yanshan Wang ◽  
Andrew Wen ◽  
Liwei Wang ◽  
Na Hong ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Data Model ◽  
Structured Data ◽  
Common Data Model ◽  
Concept System ◽  
Unstructured Text ◽  
Electronic Health

BACKGROUND Widespread adoption of electronic health records has enabled the secondary use of electronic health record data for clinical research and health care delivery. Natural language processing techniques have shown promise in their capability to extract the information embedded in unstructured clinical data, and information retrieval techniques provide flexible and scalable solutions that can augment natural language processing systems for retrieving and ranking relevant records. OBJECTIVE In this paper, we present the implementation of a cohort retrieval system that can execute textual cohort selection queries on both structured data and unstructured text—Cohort Retrieval Enhanced by Analysis of Text from Electronic Health Records (CREATE). METHODS CREATE is a proof-of-concept system that leverages a combination of structured queries and information retrieval techniques on natural language processing results to improve cohort retrieval performance using the Observational Medical Outcomes Partnership Common Data Model to enhance model portability. The natural language processing component was used to extract common data model concepts from textual queries. We designed a hierarchical index to support the common data model concept search utilizing information retrieval techniques and frameworks. RESULTS Our case study on 5 cohort identification queries, evaluated using the precision at 5 information retrieval metric at both the patient-level and document-level, demonstrates that CREATE achieves a mean precision at 5 of 0.90, which outperforms systems using only structured data or only unstructured text with mean precision at 5 values of 0.54 and 0.74, respectively. CONCLUSIONS The implementation and evaluation of Mayo Clinic Biobank data demonstrated that CREATE outperforms cohort retrieval systems that only use one of either structured data or unstructured text in complex textual cohort queries.

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