Intakosum, Sarun

Preferred name

Intakosum, Sarun

Main Affiliation

School of Science

sarun.in@kmitl.ac.th

Now showing 1 - 10 of 16

Some of the metrics are blocked by your
consent settings
XER: A recommendation for XML element
(2010-08-11)
Vacharaskunee, Sutheetutt
;
Intakosum, Sarun
The strong point of the XML is that it allows document owners to describe their documents in their own format (structure and element names). There might be the same information has been describe in various ways. When user wants to search some information from XML documents, user might not retrieve all related results because of the difference of elements (tag names). To retrieve all related results, user needs to have queries for all possible elements. XML Element Recommendation (XER) is an idea to make XML documents easier for searching. It receives XML document as an input and compares that input with XML documents from database. It compares word similarity and semantic of each element. For semantic similarity of each element, it checks those elements to find which element (word) should be used by using word ranking (most common words). The output is a recommendation for each element of input XML document. © 2010 IEEE.
Some of the metrics are blocked by your
consent settings
Adaptation of design pattern retrieval using CBR and FCA
(2009-12-01)
Muangon, Weenawadee
;
Intakosum, Sarun
Software developers currently find design patterns through search tools for solving software design problem. However, these search tools still have keywordsearch problem. In this paper, we introduce the elementary idea to improve the design pattern retrieval tool. We propose the combination of Case Based Reasoning (CBR) and Formal Concept Analysis (FCA). Because of CBR lead to the smart solution and FCA provides flexible way to maintain indexing in the case base. © 2009 IEEE.
Some of the metrics are blocked by your
consent settings
Unleashing Hidden Business Insights: Harnessing Unstructured Big Data through Text Analysis, NLP, and Visualizations for Budgetary Decisions in Governmental Organizations
(2024-01-01)
Kongthong, Chanwit
;
Jitkajornwanich, Kulsawasd
;
Intakosum, Sarun
Processing Thai language texts can be a challenge due to the complexities of the language, particularly texts from social media and online platforms. This paper introduces an analysis and visualization framework specifically designed to tackle the intricacies associated with processing the Thai language data within the context of online textual content, by utilizing natural language processing (NLP) and visualization techniques. The objectives of this study were to develop an effective Thai text data analysis and visualization framework that allows us to effectively and automatically get a better understanding of the content embedded in Thai textual data. The methodology initiated with a review of existing analysis frameworks and visualization techniques with a specific focus on Thai. The data collection phase encompassed a diverse corpus of Thai text data gathered from online sources. The selected data underwent preprocessing to address language-specific challenges. The proposed Thai analysis and visualization framework consists of multiple stages. Each stage is tailored to accommodate the intricacies of the Thai language, facilitating improved information extraction and text comprehension. The proposed visualization techniques utilize interactive graphs, such as bar charts, line charts, pie charts and donut charts, to offer intuitive and insightful representations of the processed data. Results from our case study show the effectiveness of our Thai analysis framework and visualization techniques in capturing crucial information from online contents written in Thai from governmental organizations.
Some of the metrics are blocked by your
consent settings
From use cases to framelets for building application frameworks
(2008-05-27)
Intakosum, Sarun
Framework-based software development has been proven a useful technique to develop an application. However, the development of a large application framework itself is considered complex. There are two major causes for this problem, the size of a framework and the vague framework requirements. The idea of framelet a small but complete framework, can be applied to solve the former. The Framelet-based Approach for Framework Development (FAFD) has been proposed to address the later. There are some improvements in term of use case requirements description to the approach after it was first presented. This paper aims to report such improvements as well as the ongoing researches on the FAFD. © 2008 IEEE.
Some of the metrics are blocked by your
consent settings
XML element recommendation by semantic ranking
(2010-05-28)
Vacharaskunee, Sutheetutt
;
Intakosum, Sarun
From the strong point of XML that allows document owners to describe their documents in their own format, it is difficult to search information if those XML documents use different formats. Moreover, users might not retrieve all relevant information from differently formatted XML documents. To allow users to retrieve all relevant results, users need to have as many as queries for all possible formats. SXER (Semantic Ranking for XML Element Recommendation) is an idea to make XML documents easier for searching. It receives XML document as an input, checks all possible semantics for each element, and checks those semantic elements to find which element (word) should be used. The output is a recommendation for each element of input XML document. ©2010 IEEE.
Some of the metrics are blocked by your
consent settings
An approach to XML tag recommendation
(2011-01-01)
Vacharaskunee, Sutheetutt
;
Intakosum, Sarun
The one strong point of XML is that it allows document owners to create their own structure and tag names. It might be that some XML documents contain the same information but use a different structure and/or tag names that have the same meaning but in different words. It will be difficult not only to search all relevant information in one query but also to use exchanged information right away. If the sender and receiver use different formats of XML, then either the sender or receiver has to reformat his XML. The best way to make searching and/or exchanging information easier is to ensure that all XML documents are in the same format. XML Tag Recommendation (XTR) is introduced to support this idea. XTR is based on case-based reasoning framework. It collects the most used tag name as a solution for future use. When you insert a new problem to XTR, it finds the most similar case and recommends the solution from that case to the XML document owner. The XML document owner can change his document format into the recommended solution format. Thus, the XML documents are in the same format. This makes searching and/or exchanging information more powerful. © 2011 IEEE.
Some of the metrics are blocked by your
consent settings
OPI model: A methodology for development metric based on outcome oriented
(2011-07-21)
Thammarak, Kaenchan
;
Intakosum, Sarun
Metric is extremely important for software development. It is a tool for measuring software in both quantitative and qualitative aspects. In addition, metric can be used for determining an achievement of the goals. There are some problems that bring difficulties to the design and development of software metrics. Among them, a number of software perspectives that metrics must handle and the way to apply metrics results to support business outcomes are considered important. This paper proposes OPI as a model for implementing software metrics based on business outcomes. There are three steps in this model, defining outcomes (O), defining perspectives (P), and defining indicators (I). A case study has been developed to assess the use of the proposed model. Forty undergraduate students, who have basic knowledge in software metric, use the model to develop metrics from the case study. The preliminary evaluation is based on usability aspect. The result has show that 85 percents of the students think that the model is easy to understand, where 8 and 7 percents say that it is moderate and hard respectively. © 2011 IEEE.
Some of the metrics are blocked by your
consent settings
Discovery of association rules between factors affecting user satisfaction in software project by FP-GROWTH Algorithm
(2021-05-19)
Kaewbanjong, Katawut
;
Intakosum, Sarun
The main objective of this work was to find the association rules between factors affecting user satisfaction in software project by using an association rule discovery technique. Data from 191 software projects were collected and association rules between 15 Selected factors were discovered by FP-growth algorithm. Primarily, 281 association rules were discovered. Rules that were not directly related to user satisfaction were filtered out by simple criteria. In the end, 11 final association rules that passed those criteria were obtained with an average confidence value of 65.30%. These rules can incorporated in the planning and administration of a software project to gain utmost user satisfaction
Some of the metrics are blocked by your
consent settings
Statistical Analysis with Prediction Models of User Satisfaction in Software Project Factors
(2020-06-01)
Kaewbanjong, Katawut
;
Intakosum, Sarun
We analyzed a volume of software project data and found significant user satisfaction in several software project factors. statistical significance A analysis (logistic regression) a collinearity analysis and determined the significance factors from a group of 71 pre-defined factors from 191 software projects in ISBSG Release 12. Eight prediction models were used to test the prediction potential of these factors: Neural network, k-NN, Naïve Bayes, Random forest, Decision tree, Gradient boosted tree, linear regression and logistic regression prediction model. Fifteen pre-defined factors were significant in predicting user satisfaction: client-server, personnel changes, total defects delivered, project inactive time, industry sector, application type, development type, how methodology was acquired, development techniques, decision making process, intended market, size estimate approach, size estimate method, cost recording method, and effort estimate method. They provided 82.71% prediction accuracy when used with a neural network prediction model. These findings may directly benefit software development managers.
Some of the metrics are blocked by your
consent settings
Improving OpenAI's Whisper Model for Transcribing Homophones in Legal News
(2024-01-01)
Siriket, Lattapon
;
Jitkajornwanich, Kulsawasd
;
Jaiyen, Saichon
;
Intakosum, Sarun
The 'Whisper' model provides a tool for those who require transcription of human voice. It equips with opensource features and diverse functionalities. The model is capable of effectively deciphering messages in multiple languages, including support for the Thai language. This paper focuses on improving the transcription process of Thai homophones using the Whisper model in reducing the word error rate (WER). We focus on words in the legal news category and identify factors that lead to Whisper's incorrect sound predictions. We examined homophones using snippets of legal news video clips and compiled them into a homophone dictionary. We compare words extracted from the Whisper model by determining the word error rate and spelling of words. Based on the initial results obtained from the original Whisper model and the created homophone dictionary, 48 % of the words were incorrectly transcribed out of a total of 94 words. Then, we propose a methodology by which the performance of the Whisper is improved. That way, the automatic speech recognition of Thai language using the Whisper model can fully be utilized and used in other applications.

Intakosum, Sarun

Filters

Settings

Sort By

Results per page