Transformation of Extracted Knowledge in Malay Unstructured Documents Into an Interrogative Structured Form

The availability of knowledge discovery operation helps to extract valuable information and knowledge in large volumes of data in structured databases. However, a large portion of the available information is not in structured form but rather collections of text documents in unstructured format, which also implies to Malay unstructured documents. Therefore, structuring characteristics must be imposed to unstructured documents in order to transform information available in unstructured documents into knowledge. A new approach has been established to transform extracted knowledge in Malay unstructured document by identifying, organizing, and structuring them into interrogative structured form. Its architecture is developed based on the implementation of (i) interrogative knowledge identification; (ii) interrogative contextual information; and (iii) interrogative knowledge organization and structuring with Malay knowledge representation by concepts. It utilizes the Malay language corpus; interrogative theory; as well as object-oriented, ontology, and database model. The research involves system development based on architecture of the MalaylK-Ontology, which is being measured by quantitative retrieval performance using the recall and precision metrics. The development of the Retrieval lnterrogative Ontology Analysis Application is used to verify fitness of task for the functionalities and usefulness on the utilization of interrogative contextual information with color coding supplement, additional information annotation, and Malay knowledge representation by concepts. A number of experiments are carried out to quantify the accuracy of knowledge extracted. The MalaylK-Ontology is tested by using stratified random sampling drawn from various sources of Malay unstructured documents such as news, e-mails, articles, magazines, and texts from children story books. The results of the experiments have proved that the approach of MalaylK-Ontology performed well as compared to knowledge extracted manually done by an expert. The results of questionnaires evaluation on the Retrieval lnterrogative Ontology Analysis Application have shown good achievement in understanding the main point of the unstructured document easily and clearly. This is to improve better understanding the process of making sense of information into knowledge, maintaining the meaning of the information and gaining the interpretation of the identical knowledge in unstructured document which facilitate identical knowledge perceived by different people

MalayIK: An Ontological Approach to Knowledge Transformation in Malay Unstructured Documents

The number of unstructured documents written in Malay language is enormously available on the web and intranets. However, unstructured documents cannot be queried in simple ways, hence the knowledge contained in such documents can neither be used by automatic systems nor could be understood easily and clearly by humans. This paper proposes a new approach to transform extracted knowledge in Malay unstructured document using ontology by identifying, organizing, and structuring the documents into an interrogative structured form. A Malay knowledge base, the MalayIK corpus is developed and used to test the MalayIK-Ontology against Ontos, an existing data extraction engine. The experimental results from MalayIK-Ontology have shown a significant improvement of knowledge extraction over Ontos implementation. This shows that clear knowledge organization and structuring concept is able to increase understanding, which leads to potential increase in sharable and reusable of concepts among the community

Protecting wireless data transmission in mobile application systems using digital watermarking technique

There have been many cases of fake documents be used for important legal transactions. This includes the use of fake degrees or certificates during professional job applications either in private sectors or government related firms. Since many people are using smart phones currently, it is possible to have a mobile application system apps that can validate the correctness of legal documents or certificates in real time basis. The apps must be able to validate the certificate by confirming it with the data obtained from a registered database owned by relevant academic institutions. However, since these data require wireless transmissions which are vulnerable to data manipulations by hackers, this paper introduces a protection measure using encrypted elements of user authentication to watermark the transmitting data

Skyline queries over incomplete multidimensional database

In recent years, there has been much focus on skyline queries that incorporate and provide more flexible query operators that return data items which are dominating other data items in all attributes (dimensions).Several techniques for skyline have been proposed in the literature.Most of the existing skyline techniques aimed to find the skyline query results by supposing that the values of dimensions are always present for every data item.In this paper we aim to evaluate the skyline preference queries in which some dimension values are missing.We proposed an approach for answering preference queries in a database by utilizing the concept of skyline technique.The skyline set selected for a given query operation is then optimized so that the missing values are replaced with some approximate values that provide a skyline answer with complete data.This will significantly reduce the number of comparisons between data items.Beside that, the number of retrieved skyline data items is reduced and this guides the users to select the most appropriate data items from the several alternative complete skyline data items

Preference evaluation techniques of preference queries in database

Preference queries are considered as a major necessity tool in today’s database management system (DBMS). Adopting preference queries in the database application systems enable users to determine more than one objective in the submitted query which result into more accurate results compared to the traditional queries. Preference queries prefer one data item (tuple) p over the other data item (tuple) q if and only if p is better than q in all dimensions (attributes) and not worse than q in at least one dimension (attribute). Several preference evaluation techniques for preference queries have been proposed which aimed at finding the “best” results that meet the user preferences. These include but not limited to top-k, skyline, ranked skylines, k-representative dominance, k-dominance,top-k dominating, and k-frequency. This paper attempts to survey and analyze the following preference evaluation techniques of query processing in database systems: top-k, skyline, top-k dominating, k-dominance, and k-frequency by highlighting the strengths and the weaknesses of each technique

Policy inconsistency detection bassed on RBAC model in cross-organizational collaboration

Policy integration and conflict resolutions among various organizations still remain a major challenge.Moreover, policy inconsistency detection approach with logical reasoning techniques which considers integration requirements from collaboration parties has not been well studied.In this paper, we proposed a model to detect inconsistencies based on role-based access control (RBAC) that considers role hierarchy (RH) and temporal and spatial constraints.A model to prune and collect only the required policies based on access control requirements from different organizations is designed.Policy inconsistency detection should be enhanced with logical-based analysis in order to develop security policy integration.We believe this work could provide manner to filter a large amount of unrelated policies and only return potential collaboration policies for conflict resolution

Missing values estimation for skylines in incomplete database

Incompleteness of data is a common problem in many databases including web heterogeneous databases, multi-relational databases, spatial and temporal databases and data integration. The incompleteness of data introduces challenges in processing queries as providing accurate results that best meet the query conditions over incomplete database is not a trivial task. Several techniques have been proposed to process queries in incomplete database. Some of these techniques retrieve the query results based on the existing values rather than estimating the missing values. Such techniques are undesirable in many cases as the dimensions with missing values might be the important dimensions of the user’s query. Besides, the output is incomplete and might not satisfy the user preferences. In this paper we propose an approach that estimates missing values in skylines to guide users in selecting the most appropriate skylines from the several candidate skylines. The approach utilizes the concept of mining attribute correlations to generate an Approximate Functional Dependencies (AFDs) that captured the relationships between the dimensions. Besides, identifying the strength of probability correlations to estimate the values. Then, the skylines with estimated values are ranked. By doing so, we ensure that the retrieved skylines are in the order of their estimated precision

A systematic literature review of computer ethics issues

Given the importance and concern of computer ethics, four issues have been identified in the field of computer and Information Technology (IT). This study was carried out to review the work done on computer ethics issues for the years 2010 to 2014. This paper identifies the methods used, topics addressed, and the main findings published of the research about ethical issues in computer usage. Systematic literature review (SLR) has been conducted according to the standard guidelines, and a study protocol was applied to answer three research questions: 1) What are the ethical issues in computer ethics that have been discussed in previous research?, 2) What are the most recent topics among computer ethics issues?, and 3) To what extent does investigation among IT students, Non-IT students and IT professionals display different perceptions of IT issues? Based on the evidence extracted from 40 studies, it has been clearly stated that software piracy in Privacy, Accuracy, Property and Accessibility (PAPA) and general issues are the topics most frequently discussed. It shows the gaps in the current literature pertaining to computer ethical issues and in particular, the issue of software piracy

Optimizing title and Meta tags based on distribution of keywords; Lexical and semantic approaches

Problem statement: To increase traffic on websites, Search Engine Optimization (SEO) has provided many costly and time-consuming options. One problem is the inadequate distribution of keywords especially those keywords that users use the title tag and Meta tags. Approach: This study described work on an initial model for handling some of the SEO factors to increase the distribution of keywords. Our purposed model provide users with the words and their values based on the key weights with initiated formula to provide a new title, keywords, or description in order to increase the relativity between content and HTML Meta tags and title tag. Results: The proposed model had been showed evidence of gaining the greater utilization of the distribution of keywords and prevents recognition of search engine spam. Conclusion: The result shows the significant enhancement of the proposed model on Title Weight by 51.69% of original Title Weight defined by user

Efficient skyline processing algorithm over dynamic and incomplete database

The notion of skyline processing is to discover the data items that are not dominated by any other data items. It is a well-known technique that is utilised to determine the best results that meet the user’s preferences. However, the rapid growth and frequent changes of data make the process of identifying skyline points no longer a trivial task. Most of the existing skyline approaches assume that the database is complete and static. However, in real world scenario, this assumption is not valid especially in multidimensional databases in which some dimensions have missing values while they are dynamic due to the continual modifications made towards them. Blindly examining the whole database after changes are made to identify the skyline points is inappropriate as not all data items are affected by the changes. Hence, in this study we propose a skyline algorithm, DyIn-Skyline, which is capable of identifying skyline points over dynamic and incomplete databases, by exploiting only those data items that are affected by the changes. Several experiments have been conducted and the results show that our proposed algorithm outperforms the previous work by reducing the number of pairwise comparisons in the range of 50% to 73%