scholarly journals Retrieving Model for Design Patterns

1970 ◽  
Vol 3 (1) ◽  
pp. 51-55
Author(s):  
Sarun Intakosum ◽  
Weenawadee Muangon
Keyword(s):  
Design Patterns ◽  
Vector Space Model ◽  
Weight Vector ◽  
Problem Domain ◽  
Design Problems ◽  
Space Model ◽  
Proposed Model ◽  
The Right ◽  
Index Weight ◽  
Correct Design

The purpose of this research is to develop a retrieving model for design patterns, based on problem domain context. The research aims to provide a convenient way for developers to access to the right design patterns that can solve their design problems. The proposed model is composed of two major parts, the analysis of design pattern documents to create searchindexes, and the calculation of index weight. Vector space model is used to calculate similarity between queries and documents. The result of this research shows that precision of the proposed model, in retrieving correct design patterns, is about 70 percents in average.

The uncertainty mapping of ontologies based on three-dimensional combination weight vector space model

2018 ◽  
Vol 46 (2) ◽  
pp. 110-119
Author(s):  
Dongmei Han ◽  
Wen Wang ◽  
Suyuan Luo ◽  
Weiguo Fan ◽  
Songxin Wang
Keyword(s):  
Vector Space ◽  
Three Dimensional ◽  
Vector Space Model ◽  
Weight Vector ◽  
Mapping Method ◽  
Membership Degree ◽  
Content Type ◽  
Space Model ◽  
Pcr Method ◽  
Uncertainty Mapping

Purpose This paper aims to apply vector space model (VSM)-PCR model to compute the similarity of Fault zone ontology semantics, which verified the feasibility and effectiveness of the application of VSM-PCR method in uncertainty mapping of ontologies. Design/methodology/approach The authors first define the concept of uncertainty ontology and then propose the method of ontology mapping. The proposed method fully considers the properties of ontology in measuring the similarity of concept. It expands the single VSM of concept meaning or instance set to the “meaning, properties, instance” three-dimensional VSM and uses membership degree or correlation to express the level of uncertainty. Findings It provides a relatively better accuracy which verified the feasibility and effectiveness of VSM-PCR method in treating the uncertainty mapping of ontology. Research limitations/implications The future work will focus on exploring the similarity measure and combinational methods in every dimension. Originality/value This paper presents an uncertain mapping method of ontology concept based on three-dimensional combination weighted VSM, namely, VSM-PCR. It expands the single VSM of concept meaning or instance set to the “meaning, properties, instance” three-dimensional VSM. The model uses membership degree or correlation which is used to express the degree of uncertainty; as a result, a three-dimensional VSM is obtained. The authors finally provide an example to verify the feasibility and effectiveness of VSM-PCR method in treating the uncertainty mapping of ontology.

Research on Combined Weight of Target Threat Index of Information Fusion

2014 ◽  
Vol 599-601 ◽  
pp. 1629-1635
Author(s):  
Ke Hu Xu ◽  
Jin Yu Chen ◽  
De Peng Kong
Keyword(s):  
Information Fusion ◽  
Weight Vector ◽  
Vector Model ◽  
Weight Optimization ◽  
Threat Index ◽  
Minimal Deviation ◽  
The Right ◽  
Index Weight ◽  
Optimal Weight Vector ◽  
Deviation Method

To the characteristics of index weight, using minimal deviation method as the theoretical tools to create index portfolio weight optimization model. Using genetic algorithms to solve the optimal weight vector model which has the capability of global searching . Through example demonstrate, the right combination to get the weight vector of the model is more reasonable and scientific, and genetic algorithm process a simpler and easier way to understand than traditional methods.

A Search Of File Journal With Query Word on List of Journal Document List Using VectorSpace Model Method

2020 ◽  
Vol 9 (1) ◽  
pp. 97
Author(s):  
Maula Khatami
Keyword(s):  
Vector Space ◽  
Suffix Tree ◽  
Vector Space Model ◽  
Inverse Document Frequency ◽  
Space Model ◽  
Model Method ◽  
Document Frequency ◽  
New Knowledge ◽  
Query Word ◽  
The Right

Journals are articles about research that are very useful among academics and students alike. Every time we learn a new knowledge, we certainly need a guide that is verified and also credible. Students and academics were greatly helped by this journal. With journals help students and academics get references from previous research and get more insights so that they are able to make a related research and can even be improved from previous research. However, there are still many students and academics who find it difficult to find the right journal for their needs. So here the authors make a research system of information retrieval about journal searches by querying words using the vector space model method. In the suffix tree clustering method and the Vector Space Model, each document and keyword that has been carried out by the Text Mining process is then given the weight of each word contained in each existing document with the Term Frequency - Inverse Document Frequency (TF-IDF) weighting algorithm. 

An ontology-improved vector space model for semantic retrieval

2020 ◽  
Vol 38 (5/6) ◽  
pp. 919-942
Author(s):  
Mingwei Tang ◽  
Jiangping Chen ◽  
Haihua Chen ◽  
Zhenyuan Xu ◽  
Yueyao Wang ◽  
...  
Keyword(s):  
Vector Space ◽  
Vector Space Model ◽  
Semantic Retrieval ◽  
Tree Model ◽  
Content Type ◽  
Space Model ◽  
Whole Process ◽  
Proposed Model ◽  
Digital Collection ◽  
Semantic Ontology

Purpose The purpose of this paper is to provide an integrated semantic information retrieval (IR) solution based on an ontology-improved vector space model for situations where a digital collection is established or curated. It aims to create a retrieval approach which could return the results by meanings rather than by keywords. Design/methodology/approach In this paper, the authors propose a semantic term frequency algorithm to create a semantic vector space model (SeVSM) based on ontology. To support the calculation, a multi-branches tree model is created to represent the ontology and a set of algorithms is developed to operate it. Then, a semantic ontology-based IR system based on the SeVSM model is designed and developed to verify the effectiveness of the proposed model. Findings The experimental study using 30 queries from 15 different domains confirms the effectiveness of the SeVSM and the usability of the proposed system. The results demonstrate that the proposed model and system can be a significant exploration to enhance IR in specific domains, such as a digital library and e-commerce. Originality/value This research not only creates a semantic retrieval model, but also provides the application approach via designing and developing a semantic retrieval system based on the model. Comparing with most of the current related research, the proposed research studies the whole process of realizing a semantic retrieval.

Improving Document Retrieval with Spelling Correction for Weak and Fabricated Indonesian-Translated Hadith

2020 ◽  
Vol 4 (3) ◽  
pp. 551-557
Author(s):  
Muhammad zaky ramadhan ◽  
Kemas Muslim Lhaksmana
Keyword(s):  
Retrieval System ◽  
Islamic Law ◽  
Vector Space Model ◽  
Document Retrieval ◽  
The Internet ◽  
Average Precision ◽  
Spelling Correction ◽  
Space Model ◽  
The Mean ◽  
The Web

Hadith has several levels of authenticity, among which are weak (dhaif), and fabricated (maudhu) hadith that may not originate from the prophet Muhammad PBUH, and thus should not be considered in concluding an Islamic law (sharia). However, many such hadiths have been commonly confused as authentic hadiths among ordinary Muslims. To easily distinguish such hadiths, this paper proposes a method to check the authenticity of a hadith by comparing them with a collection of fabricated hadiths in Indonesian. The proposed method applies the vector space model and also performs spelling correction using symspell to check whether the use of spelling check can improve the accuracy of hadith retrieval, because it has never been done in previous works and typos are common on Indonesian-translated hadiths on the Web and social media raw text. The experiment result shows that the use of spell checking improves the mean average precision and recall to become 81% (from 73%) and 89% (from 80%), respectively. Therefore, the improvement in accuracy by implementing spelling correction make the hadith retrieval system more feasible and encouraged to be implemented in future works because it can correct typos that are common in the raw text on the Internet.

Aplikasi Deteksi Kemiripan Tugas Paper

2017 ◽  
Vol 15 (2) ◽  
pp. 5
Author(s):  
Anthony Anggrawan ◽  
Azhari
Keyword(s):  
Information Retrieval ◽  
Vector Space ◽  
Vector Space Model ◽  
Mean Average Precision ◽  
Average Precision ◽  
Information Searching ◽  
Space Model ◽  
Model Method

Information searching based on users’ query, which is hopefully able to find the documents based on users’ need, is known as Information Retrieval. This research uses Vector Space Model method in determining the similarity percentage of each student’s assignment. This research uses PHP programming and MySQL database. The finding is represented by ranking the similarity of document with query, with mean average precision value of 0,874. It shows how accurate the application with the examination done by the experts, which is gained from the evaluation with 5 queries that is compared to 25 samples of documents. If the number of counted assignments has higher similarity, thus the process of similarity counting needs more time, it depends on the assignment’s number which is submitted.

Aplikasi Rekomendasi Buku Pada Katalog Perpustakaan Universitas Multimedia Nusantara Menggunakan Vector Space Model

2018 ◽  
Vol 9 (2) ◽  
pp. 97-105
Author(s):  
Richard Firdaus Oeyliawan ◽  
Dennis Gunawan
Keyword(s):  
Vector Space ◽  
Vector Space Model ◽  
Vector Model ◽  
Library Management ◽  
Space Model ◽  
Library Management System ◽  
Index Terms ◽  
Library Catalogue ◽  
Language Sample ◽  
F Measure

Library is one of the facilities which provides information, knowledge resource, and acts as an academic helper for readers to get the information. The huge number of books which library has, usually make readers find the books with difficulty. Universitas Multimedia Nusantara uses the Senayan Library Management System (SLiMS) as the library catalogue. SLiMS has many features which help readers, but there is still no recommendation feature to help the readers finding the books which are relevant to the specific book that readers choose. The application has been developed using Vector Space Model to represent the document in vector model. The recommendation in this application is based on the similarity of the books description. Based on the testing phase using one-language sample of the relevant books, the F-Measure value gained is 55% using 0.1 as cosine similarity threshold. The books description and variety of languages affect the F-Measure value gained. Index Terms—Book Recommendation, Porter Stemmer, SLiMS Universitas Multimedia Nusantara, TF-IDF, Vector Space Model

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