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Semantic Similarity Assessment of Volunteered Geographic Information

The recent development in communication technologies between individuals allows for the establishment of more informal collaborative map data projects which are called volunteered geographic information (VGI). These projects, such as OpenStreetMap (OSM) project, seek to create free alternative maps which let users add or input new materials to the data of others. The information of different VGI data sources is often not compliant to any standard and each organization is producing a dataset at various level of richness. In this research the assessment of semantic data quality provided by web sources, e.g. OSM will depend on a comparison with the information from standard sources. This will include the validity of semantic accuracy as one of the most important parameter of spatial data quality parameters. Semantic similarity testing covered feature classification, in effect comparing possible categories (legend classes) and actual attributes attached to features. This will be achieved by developing a tool, using Matlab programming language, for analysing and examining OSM semantic accuracy. To identify the strength of semantic accuracy assessment strategy, there are many factors should be considered. For instance, the confusion matrix of feature classifications can be assessed, and different statistical tests should be passed. The results revealed good semantic accuracy of OSM datasets.

 

 

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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Publication Date
Mon Oct 03 2022
Journal Name
International Journal Of Interactive Mobile Technologies (ijim)
A New Feature-Based Method for Similarity Measurement under the Linux Operating System

This paper presents a new algorithm in an important research field which is the semantic word similarity estimation. A new feature-based algorithm is proposed for measuring the word semantic similarity for the Arabic language. It is a highly systematic language where its words exhibit elegant and rigorous logic. The score of sematic similarity between two Arabic words is calculated as a function of their common and total taxonomical features. An Arabic knowledge source is employed for extracting the taxonomical features as a set of all concepts that subsumed the concepts containing the compared words. The previously developed Arabic word benchmark datasets are used for optimizing and evaluating the proposed algorithm. In this paper,

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Publication Date
Mon Oct 28 2019
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
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Publication Date
Mon May 28 2018
Journal Name
Iraqi Journal Of Science
M A Modified Similarity Measure for Improving Accuracy of User-Based Collaborative Filtering: Nadia Fadhil

Production sites suffer from idle in marketing of their products because of the lack in the efficient systems that analyze and track the evaluation of customers to products; therefore some products remain untargeted despite their good quality. This research aims to build a modest model intended to take two aspects into considerations. The first aspect is diagnosing dependable users on the site depending on the number of products evaluated and the user's positive impact on rating. The second aspect is diagnosing products with low weights (unknown) to be generated and recommended to users depending on logarithm equation and the number of co-rated users. Collaborative filtering is one of the most knowledge discovery techniques used positive

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Publication Date
Tue Mar 31 2020
Journal Name
College Of Islamic Sciences
The semantic use of Emiri discourse in the story of Joseph

   The term discourse is one of the terms that have attracted the attention of learners because it is indicative of the speech that is directly related to the addressee and the addressee through a common message between them. In the story of the study and the importance of research can be a widespread method, and then the choice of this story the story of Joseph (peace be upon him) in particular did not come The research presented in the introduction and the preamble and three topics, dealt with the definition of discourse, and the role of discourse in modern Quranic and linguistic studies, and in the first section dealt with the definition of the style of command language, terminology and command formu

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi Journal Of Science
Using Retrieved Sources for Semantic and Lexical Plagiarism Detection

     Plagiarism is described as using someone else's ideas or work without their permission. Using lexical and semantic text similarity notions, this paper presents a plagiarism detection system for examining suspicious texts against available sources on the Web. The user can upload suspicious files in pdf or docx formats. The system will search three popular search engines for the source text (Google, Bing, and Yahoo) and try to identify the top five results for each search engine on the first retrieved page. The corpus is made up of the downloaded files and scraped web page text of the search engines' results. The corpus text and suspicious documents will then be encoded as vectors. For lexical plagiarism detection, the system will

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
3D scenes semantic segmentation using deep learning based Survey
Abstract<p>Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po</p> ... Show More
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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
The Semantic Relation among the Expressions Of the Phonetic in the Holy Qura: The Semantic Relation among the Expressions Of the Phonetic in the Holy Qura

Abstract
The phonetic replacement is the process of putting a sound or a linguistic
syllable instead of another in one word that results in changing its meaning . It is one
way of vocabulary varionsness and discrimination because replacement among the
sounds of one expression and changing its image lead to change its meaning , and
accordingly , each replaced sound has its own linguistic value that distinguishes it . In
other words , the phonetic replacement is based on system of phonemic change
which is a general phenomenon in all languages . The linguistic system doesn’t stand
straight for word unless it is based on different standards that work on variousness ,
assortment and relating the phonetic change wi

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
Automatic Short Answer Grading System Based on Semantic Networks and Support Vector Machine

      In education, exams are used to asses students’ acquired knowledge; however, the manual assessment of exams consumes a lot of teachers’ time and effort. In addition, educational institutions recently leaned toward distance education and e-learning due the Coronavirus pandemic. Thus, they needed to conduct exams electronically, which requires an automated assessment system. Although it is easy to develop an automated assessment system for objective questions. However, subjective questions require answers comprised of free text and are harder to automatically assess since grading them needs to semantically compare the students’ answers with the correct ones. In this paper, we present an automatic short answer grading metho

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Publication Date
Fri Jun 02 2023
Journal Name
Alustath Journal For Human And Social Sciences