Development of bambangan (Mangifera pajang) carbonated drink

Mangifera pajang Kostermans or bambangan is a popular fruit among Sabahan due to its health and economic values. However, the fruit is not fully commercialized since it is usually been used as traditional cuisine by local people. Thus, development of bambangan fruit into carbonated drink was conducted to produce new product concept. The objectives of this study were to conceptualize, formulate, evaluate consumer acceptance, and determine physicochemical properties and nutritional composition of the accepted product. Method used in conceptualising the product was based on questionnaire. The consumer acceptance was evaluated based on descriptive and affective tests with four product formulations tested. The physicochemical properties on carbon dioxide volume, colour, pH, total acidity, total soluble solid (TSS) and viscosity were highlighted, meanwhile nutritional composition on fat, protein, carbohydrates and energy content were determined. About 77% respondents gave positive feedback, and 69% respondents decided this product is within their budget. The formulation of 5% bambangan pulp, 70% water, 25% sugar and 0.2% citric acid was highly accepted in descriptive and affective tests with 4.4 and 6.39 mean scores, respectively. The physicochemical properties and nutritional composition of the acceptance product were in optimum value except for colour, total acidity and TSS. Overall, this study showed that the product has high potential to be commercialized as new product concept, and heritage of indigenous people can be preserved when this fruit is known regionally

Applications of concurrent access patterns in web usage mining

This paper builds on the original data mining and modelling research which has proposed the discovery of novel structural relation patterns, applying the approach in web usage mining. The focus of attention here is on concurrent access patterns (CAP), where an overarching framework illuminates the methodology for web access patterns post-processing. Data pre-processing, pattern discovery and patterns analysis all proceed in association with access patterns mining, CAP mining and CAP modelling. Pruning and selection of access pat-terns takes place as necessary, allowing further CAP mining and modelling to be pursued in the search for the most interesting concurrent access patterns. It is shown that higher level CAPs can be modelled in a way which brings greater structure to bear on the process of knowledge discovery. Experiments with real-world datasets highlight the applicability of the approach in web navigation

Graph-based Modelling of Concurrent Sequential Patterns

Structural relation patterns have been introduced recently to extend the search for complex patterns often hidden behind large sequences of data. This has motivated a novel approach to sequential patterns post-processing and a corresponding data mining method was proposed for Concurrent Sequential Patterns (ConSP). This article refines the approach in the context of ConSP modelling, where a companion graph-based model is devised as an extension of previous work. Two new modelling methods are presented here together with a construction algorithm, to complete the transformation of concurrent sequential patterns to a ConSP-Graph representation. Customer orders data is used to demonstrate the effectiveness of ConSP mining while synthetic sample data highlights the strength of the modelling technique, illuminating the theories developed

Tracking Federated Queries in the Linked Data

Federated query engines allow data consumers to execute queries over the federation of Linked Data (LD). However, as federated queries are decomposed into potentially thousands of subqueries distributed among SPARQL endpoints, data providers do not know federated queries, they only know subqueries they process. Consequently, unlike warehousing approaches, LD data providers have no access to secondary data. In this paper, we propose FETA (FEderated query TrAcking), a query tracking algorithm that infers Basic Graph Patterns (BGPs) processed by a federation from a shared log maintained by data providers. Concurrent execution of thousand subqueries generated by multiple federated query engines makes the query tracking process challenging and uncertain. Experiments with Anapsid show that FETA is able to extract BGPs which, even in a worst case scenario, contain BGPs of original queries

Conceptual Workflow for Complex Data Integration using AXML

International audienceRelevant data for decision support systems are available everywhere and in various formats. Such data must be integrated into a unified format. Traditional data integration approaches are not adapted to handle complex data. Thus, we exploit the Active XML language for integrating complex data. Its XML part allows to unify, model and store complex data. Moreover, its services part tackles the distributed issue of data sources. Accordingly, different integration tasks are proposed as services. These services are managed via a set of active rules that are built upon metadata and events of the integration system. In this paper, we design an architecture for integrating complex data autonomously. We have also designed the workflow for data integration tasks

QueRIE: Collaborative Database Exploration

Interactive database exploration is a key task in information mining. However, users who lack SQL expertise or familiarity with the database schema face great difficulties in performing this task. To aid these users, we developed the QueRIE system for personalized query recommendations. QueRIE continuously monitors the user’s querying behavior and finds matching patterns in the system’s query log, in an attempt to identify previous users with similar information needs. Subsequently, QueRIE uses these “similar” users and their queries to recommend queries that the current user may find interesting. In this work we describe an instantiation of the QueRIE framework, where the active user’s session is represented by a set of query fragments. The recorded fragments are used to identify similar query fragments in the previously recorded sessions, which are in turn assembled in potentially interesting queries for the active user. We show through experimentation that the proposed method generates meaningful recommendations on real-life traces from the SkyServer database and propose a scalable design that enables the incremental update of similarities, making real-time computations on large amounts of data feasible. Finally, we compare this fragment-based instantiation with our previously proposed tuple-based instantiation discussing the advantages and disadvantages of each approach

Guidelines for the analysis of student web usage in support of primary educational objectives

The Internet and World Wide Web provides huge amounts of information to individuals with access to it. Information is an important driving factor of education and higher education has experienced massive adoption rates of information and communication technologies, and accessing the Web is not an uncommon practice within a higher educational institution. The Web provides numerous benefits and many students rely on the Web for information, communication and technical support. However, the immense amount of information available on the Web has brought about some negative side effects associated with abundant information. Whether the Web is a positive influence on students’ academic well-being within higher education is a difficult question to answer. To understand how the Web is used by students within a higher education institution is not an easy task. However, there are ways to understand the Web usage behaviour of students. Using established methods for gathering useful information from data produced by an institution, Web usage behaviours of students within a higher education institution could be analysed and presented. This dissertation presents guidance for analysing Web traffic within a higher educational institution in order to gain insight into the Web usage behaviours of students. This insight can provide educators with valuable information to bolster their decision-making capacity towards achieving their educational goals

Web Mining Functions in an Academic Search Application

This paper deals with Web mining and the different categories of Web mining like content, structure and usage mining. The application of Web mining in an academic search application has been discussed. The paper concludes with open problems related to Web mining. The present work can be a useful input to Web users, Web Administrators in a university environment.Database, HITS, IR, NLP, Web mining