A hybrid method of feature extraction and naive bayes classification for splitting identifiers

Nowadays, integrating natural language processing techniques on software systems has caught many researchers’ attentions. Such integration can be represented by analyzing the morphology of the source code in order to gain meaningful information. Feature location is the process of identifying specific portions of the source code. One of the most important information lies on such source code is the identifiers (e.g. Student). Unlike the traditional text processing,the identifiers in the source code is formed as multi-word such as ‘Employee-Name’. Such multi-words are not divided using white space, instead it can be formed using special characters (e.g. Employee_ID), CamelCase (e.g. EmployeeName) or using abbreviations (e.g. EmpNm). This makes the process of extracting such identifiers more challenging. Several approaches have been performed to resolve the problem of splitting multi-word identifiers. However, there is still room for improvement in terms of accuracy. Such improvement can be represented by utilizing more robust features that have the ability to analyses the morphology of identifiers. Therefore, this study aims to propose a hybrid method of feature extraction and Naïve Bayes classifier in order to separate multi-word identifiers within source code. The dataset that has been used in this study is a benchmark-annotated data that contains large number of Java codes. Multiple experiments have been conducted in order to evaluate the proposed features independently and with combinations. Results shown that the combination of all features have obtained the best accuracy by achieving 64.7% of f-measure. Such finding implies the usefulness of the proposed features in terms of discriminating multi-word identifiers

A negation query engine for complex query transformations

Natural language interfaces to ontologies allow users to query the system using natural language queries. These systems take natural language query as input and transform it to formal query language equivalent to retrieve the desired information from ontologies. The existing natural language interfaces to ontologies offer support for handling negation queries; however, they offer limited support for dealing with them. This paper proposes a negation query handling engine which can handle relatively complex natural language queries than the existing systems. The proposed engine effectively understands the intent of the user query on the basis of a sophisticated algorithm, which is governed by a set of techniques and transformation rules. The proposed engine was evaluated using the Mooney data set and AquaLog dataset, and it manifested encouraging results

Acceptance of Health Information Application in Smart National Identity Card (SNIC) Using a New I-P Framework

This study discovers a novel framework of individual level technology adoption known as I-P (Individual- Privacy) towards Smart National Identity Card health information application. Many countries introduced smart national identity card (SNIC) with various applications such as health information application embedded inside it. However, the degree to which citizens accept and use some of the embedded applications in smart national identity remains unknown to many governments and application providers as well. Moreover, the previous studies revealed that the factors of trust, perceived risk, privacy concern and perceived credibility need to be incorporated into more comprehensive models such as extended Unified Theory of Acceptance and Use of Technology known as UTAUT2. UTAUT2 is a mainly widespread and leading theory existing in the information system literature up to now. This research identifies factors affecting the citizens' behavioural intention to use health information application embedded in SNIC and extends better understanding on the relevant factors that the government and the application providers would need to consider in predicting citizens' new technology acceptance in the future. We propose a conceptual framework by combining the UTAUT2 and Privacy Calculus Model constructs and also adding perceived credibility as a new variable. The proposed framework may provide assistance to any government planning, decision, and policy makers involving e-government projects. The empirical study may be conducted in the future to provide proof and empirically validate this I-P framework

Acceptance of Health Information Application in Smart National Identity Card (SNIC) Using a New I-P Framework

This study discovers a novel framework of individual level technology adoption known as I-P (Individual- Privacy) towards Smart National Identity Card health information application. Many countries introduced smart national identity card (SNIC) with various applications such as health information application embedded inside it. However, the degree to which citizens accept and use some of the embedded applications in smart national identity remains unknown to many governments and application providers as well. Moreover, the previous studies revealed that the factors of trust, perceived risk, privacy concern and perceived credibility need to be incorporated into more comprehensive models such as extended Unified Theory of Acceptance and Use of Technology known as UTAUT2. UTAUT2 is a mainly widespread and leading theory existing in the information system literature up to now. This research identifies factors affecting the citizens' behavioural intention to use health information application embedded in SNIC and extends better understanding on the relevant factors that the government and the application providers would need to consider in predicting citizens' new technology acceptance in the future. We propose a conceptual framework by combining the UTAUT2 and Privacy Calculus Model constructs and also adding perceived credibility as a new variable. The proposed framework may provide assistance to any government planning, decision, and policy makers involving e-government projects. The empirical study may be conducted in the future to provide proof and empirically validate this I-P framework

Acceptance of Health Information Application in Smart National Identity Card (SNIC) Using a New I-P Framework

This study discovers a novel framework of individual level technology adoption known as I-P (Individual- Privacy) towards Smart National Identity Card health information application. Many countries introduced smart national identity card (SNIC) with various applications such as health information application embedded inside it. However, the degree to which citizens accept and use some of the embedded applications in smart national identity remains unknown to many governments and application providers as well. Moreover, the previous studies revealed that the factors of trust, perceived risk, privacy concern and perceived credibility need to be incorporated into more comprehensive models such as extended Unified Theory of Acceptance and Use of Technology known as UTAUT2. UTAUT2 is a mainly widespread and leading theory existing in the information system literature up to now. This research identifies factors affecting the citizens' behavioural intention to use health information application embedded in SNIC and extends better understanding on the relevant factors that the government and the application providers would need to consider in predicting citizens' new technology acceptance in the future. We propose a conceptual framework by combining the UTAUT2 and Privacy Calculus Model constructs and also adding perceived credibility as a new variable. The proposed framework may provide assistance to any government planning, decision, and policy makers involving e-government projects. The empirical study may be conducted in the future to provide proof and empirically validate this I-P framework

Improving named entity recognition accuracy for gene and protein in biomedical text literature

The task of recognising biomedical named entities in natural language documents called biomedical Named Entity Recognition (NER) is the focus of many researchers due to complex nature of such texts. This complexity includes the issues of character-level, word-level and word order variations. In this study, an approach for recognising gene and protein names that handles the above issues is proposed. Similar to the previous related works, our approach is based on the assumption that a named entity occurs within a noun group. The strength of our proposed approach lies on a Statistical Character-based Syntax Similarity (SCSS) algorithm which measures similarity between the extracted candidates and the well-known biomedical named entities from the GENIA V3.0 corpus. The proposed approach is evaluated and results are satisfied. For recognitions of both gene and protein names, we achieved 97.2% for precision (P), 95.2% for recall (R), and 96.1 for F-measure. While for protein names recognition we gained 98.1% for P, 97.5% for R and 97.7 for F-measure

Quantitative assessment of concept maps for conceptualizing domain ontologies: a case of Quran

The use of graphical knowledge representation formalisms with a representational vocabulary agreement of terms of conceptualization of the universe of discourse is a new high potential approach in the ontology engineering and knowledge management context. Initially, concept maps were used in the fields of education and learning. After that, it became popular in other areas due to its flexible and intuitive nature. It was also proven as a useful tool to improve communication in corporate environment. In the field of ontologies, concept maps were explored to be used to facilitate different aspects of ontology development. An essential reason behind this motivation is the structural resemblance of concept maps with the hierarchical structure of ontologies. This research aims to demonstrate quantitative evaluation of 4 different hypotheses related to the effectiveness of using concept maps for ontology conceptualization. The domain of Quran was selected for the purpose of this study and it was conducted in collaboration with the experts from the Centre of Quranic Research, Universiti Malaya, Kuala Lumpur, Malaysia. The results of the hypotheses demonstrated that concept mapping was easy to learn and implement for the majority of the participants. Most of them experienced improvement in domain knowledge regarding the vocabularies used to refer to the structure of organization of the Quran, namely Juz, Surah, Ayats, tafsir, Malay translation, English translation, and relationships among these entities. Therefore, concept maps instilled the element of learning through the conceptualization process and provided a platform for participants to resolve conflicting opinions and ambiguities of terms used immediately

Acceptance of Health Information Application in Smart National Identity Card (SNIC) Using a New I-P Framework

This study discovers a novel framework of individual level technology adoption known as I-P (Individual- Privacy) towards Smart National Identity Card health information application. Many countries introduced smart national identity card (SNIC) with various applications such as health information application embedded inside it. However, the degree to which citizens accept and use some of the embedded applications in smart national identity remains unknown to many governments and application providers as well. Moreover, the previous studies revealed that the factors of trust, perceived risk, privacy concern and perceived credibility need to be incorporated into more comprehensive models such as extended Unified Theory of Acceptance and Use of Technology known as UTAUT2. UTAUT2 is a mainly widespread and leading theory existing in the information system literature up to now. This research identifies factors affecting the citizens' behavioural intention to use health information application embedded in SNIC and extends better understanding on the relevant factors that the government and the application providers would need to consider in predicting citizens' new technology acceptance in the future. We propose a conceptual framework by combining the UTAUT2 and Privacy Calculus Model constructs and also adding perceived credibility as a new variable. The proposed framework may provide assistance to any government planning, decision, and policy makers involving e-government projects. The empirical study may be conducted in the future to provide proof and empirically validate this I-P framework

Online information seeking: a review of the literature in the health domain

The development of the information technology and Internet has been transforming the healthcare industry. The internet is continuously accessed to seek for health information and there are variety of sources, including search engines, health websites, and social networking sites. Providing more and better information on health may empower individuals, however, ensuring a high quality and trusted health information could pose a challenge. Moreover, there is an ever-increasing amount of information available, but they are not necessarily accurate and up to date. Thus, this paper aims to provide an insight of the models and frameworks related to online health information seeking of consumers. It begins by exploring the definition of information behavior and information seeking to provide a better understanding of the concept of information seeking. In this study, critical factors such as performance expectancy, effort expectancy, and social influence will be studied in relation to the value of seeking health information. It also aims to analyze the effect of age, gender, and health status as the moderator on the factors that influence online health information seeking, i.e. trust and information quality. A preliminary survey will be carried out among the health professionals to clarify the research problems which exist in the real world, at the same time producing a conceptual framework. A final survey will be distributed to five states of Malaysia, to solicit the feedback on the framework. Data will be analyzed using SPSS and SmartPLS 3.0 analysis tools. It is hoped that at the end of this study, a novel framework that can improve online health information seeking is developed. Finally, this paper concludes with some suggestions on the models and frameworks that could improve online health information seeking

Sentiment classification of customer reviews based on fuzzy logic

Nowadays, e-commerce is growing fast, so product reviews have grown rapidly on the web. The large number of reviews makes it difficult for manufacturers or businesses to automatically classify them into different semantic orientations (positive, negative, and neutral). Most existing method utilize a list of opinion words for sentiment classification. whereas, this paper propose a fuzzy logic model to perform semantic classifications of customers review into the following sub-classes: very weak, weak, moderate, very strong and strong by combinations adjective, adverb and verb to increase holistic the accuracy of lexicon approach. Fuzzy logic, unlike statistical data mining techniques, not only allows using non-numerical values also introduces the notion of linguistic variables. Using linguistic terms and variables will result in a more human oriented querying process