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Articles by Aida Mustapha
Total Records ( 5 ) for Aida Mustapha
  Payam Hassany Shariat Panahy , Fatimah Sidi , Lilly Suriani Affendey , Marzanah A. Jabar , Hamidah Ibrahim and Aida Mustapha
  Improving data quality is a basic step for all companies and organizations as it leads to increase opportunity to achieve top services. The aim of this study was to validate and adapt the four major data quality dimensions’ instruments in different information systems. The four important quality dimensions which were used in this study were; accuracy, completeness, consistency and timeliness. The questionnaire was developed, validated and used for collecting data on the different information system’s users. A set of questionnaire was conducted to 50 respondents who using different information systems. Inferential statistics and descriptive analysis were employed to measure and validate the factor contributing to quality improvement process. This study has been compared with related parts of previous studies; and showed that the instrument is valid to measure quality dimensions and improvement process. The content validity, reliability and factor analysis were applied on 24 items to compute the results. The results showed that the instrument is considered to be reliable and validate. The results also suggest that the instrument can be used as a basic foundation to implicate data quality for organizations manager to design improvement process.
  Payam Hassany Shariat Panahy , Fatimah Sidi , Lilly Suriani Affendey , Marzanah A. Jabar , Hamidah Ibrahim and Aida Mustapha
  Awareness of data quality dimensions and their relationships, poses new challenges to the database provider during the past two decades. Although, information systems have continuous improvement against their data problems, their success progressively depends on their methodology. This paper presents a methodology to measure, analyze and evaluate data quality dimensions by using subjective and objective measurement. Applying empirical methods and data mining techniques are steps of this methodology to improve database quality in the information systems. The applied rules and methods can be used to visualize and analyze attribute identification of the databases which is powerful and efficient to extract and reduce inconsistencies of the data. This methodology can be applied to compute other measurable quality dimensions and can help the information system providers to have intelligent and highly sophisticated opinions on creating databases.
  Mahmoud Shaker , Hamidah Ibrahim , Aida Mustapha and Lili Nurliyana Abdullah
 

Problems statement: Nowadays, many users use web search engines to find and gather information. User faces an increasing amount of various HTML information sources. The issue of correlating, integrating and presenting related information to users becomes important. When a user uses a search engine such as Yahoo and Google to seek specific information, the results are not only information about the availability of the desired information, but also information about other pages on which the desired information is mentioned. The number of selected pages is enormous. Therefore, the performance capabilities, the overlap among results for the same queries and limitations of web search engines are an important and large area of research. Extracting information from the web pages also becomes very important because the massive and increasing amount of diverse HTML information sources in the internet that are available to users and the variety of web pages making the process of information extraction from web a challenging problem.
Approach: This study proposed an approach for extracting information from HTML web pages which was able to extract relevant information from different web pages based on standard classifications.
Results: Proposed approach was evaluated by conducting experiments on a number of web pages from different domains and achieved increment in precision and F measure as well as decrement in recall.
Conclusion: Experiments demonstrated that our approach extracted the attributes besides the sub attributes that described the extracted attributes and values of the sub attributes from various web pages. Proposed approach was able to extract the attributes that appear in different names in some of the web pages.

  Aida Mustapha , Md. Nasir Sulaiman , Ramlan Mahmod and Mohd. Hasan Selamat
  Problem statement: Overgeneration-and-ranking architecture works well in written language where sentence is the basic unit. However, in spoken language where utterance is the basic unit, the disadvantage becomes critical as spoken language also render intentions, hence short strings may be of equivalent impact. Approach: In classification-and-ranking, response was deliberately chosen from dialogue corpus rather than wholly generated, such that it allows short ungrammatical utterances as long as they satisfy the intended meaning of input utterance. Because the architecture is intention-based, it adopted an open-domain knowledge representation, whereby response utterances were semantically represented using some ontology general enough for future reuse in another domain. Results: This study presented corpus-based analysis on cross-domain experimentation using different type of corpus to validate the consistency of the response classifier that delimits the searching space for ranking. The open-domain quality for classification-an-ranking architecture was tested on two mixed-initiative, transaction dialogue corpus in theater reservation and emergency planning. Results showed consistent distribution accuracies in both classification and ranking experiment, indicating that the approach is viable for cross-domain implementations. Conclusion: The ability of a response generation system to directly learn response utterances from the domain corpus suggested the possibility to build a dialogue system by feeding the learning module with a target corpus and the system learned the response behavior directly from the training corpus.
  Aida Mustapha , Md. Nasir Sulaiman , Ramlan Mahmod and Mohd. Hasan Selamat
  Problem statement: The first component in classification-and-ranking architecture is a Bayesian classifier that classifies user utterances into response classes based on their semantic and pragmatic interpretations. Bayesian networks are sufficient if data is limited to single user input utterance. However, if the classifier is able to collate features from a sequence of previous n-1 user utterances, the additional information may or may not improve the accuracy rate in response classification. Approach: This article investigates the use of dynamic Bayesian networks to include time-series information in the form of extended features from preceding utterances. The experiment was conducted on SCHISMA corpus, which is a mixed-initiative, transaction dialogue in theater reservation. Results: The results show that classification accuracy is improved, but rather insignificantly. The accuracy rate tends to deteriorate as time-span of dialogue is increased. Conclusion: Although every response utterance reflects form and behavior that are expected by the preceding utterance, influence of meaning and intentions diminishes throughout time as the conversation stretches to longer duration.
 
 
 
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