26,939 research outputs found
A Hybrid Web Recommendation System based on the Improved Association Rule Mining Algorithm
As the growing interest of web recommendation systems those are applied to
deliver customized data for their users, we started working on this system.
Generally the recommendation systems are divided into two major categories such
as collaborative recommendation system and content based recommendation system.
In case of collaborative recommen-dation systems, these try to seek out users
who share same tastes that of given user as well as recommends the websites
according to the liking given user. Whereas the content based recommendation
systems tries to recommend web sites similar to those web sites the user has
liked. In the recent research we found that the efficient technique based on
asso-ciation rule mining algorithm is proposed in order to solve the problem of
web page recommendation. Major problem of the same is that the web pages are
given equal importance. Here the importance of pages changes according to the
fre-quency of visiting the web page as well as amount of time user spends on
that page. Also recommendation of newly added web pages or the pages those are
not yet visited by users are not included in the recommendation set. To
over-come this problem, we have used the web usage log in the adaptive
association rule based web mining where the asso-ciation rules were applied to
personalization. This algorithm was purely based on the Apriori data mining
algorithm in order to generate the association rules. However this method also
suffers from some unavoidable drawbacks. In this paper we are presenting and
investigating the new approach based on weighted Association Rule Mining
Algorithm and text mining. This is improved algorithm which adds semantic
knowledge to the results, has more efficiency and hence gives better quality
and performances as compared to existing approaches.Comment: 9 pages, 7 figures, 2 table
Preprocessing and Content/Navigational Pages Identification as Premises for an Extended Web Usage Mining Model Development
From its appearance until nowadays, the internet saw a spectacular growth not only in terms of websites number and information volume, but also in terms of the number of visitors. Therefore, the need of an overall analysis regarding both the web sites and the content provided by them was required. Thus, a new branch of research was developed, namely web mining, that aims to discover useful information and knowledge, based not only on the analysis of websites and content, but also on the way in which the users interact with them. The aim of the present paper is to design a database that captures only the relevant data from logs in a way that will allow to store and manage large sets of temporal data with common tools in real time. In our work, we rely on different web sites or website sections with known architecture and we test several hypotheses from the literature in order to extend the framework to sites with unknown or chaotic structure, which are non-transparent in determining the type of visited pages. In doing this, we will start from non-proprietary, preexisting raw server logs.Knowledge Management, Web Mining, Data Preprocessing, Decision Trees, Databases
Binary Particle Swarm Optimization based Biclustering of Web usage Data
Web mining is the nontrivial process to discover valid, novel, potentially
useful knowledge from web data using the data mining techniques or methods. It
may give information that is useful for improving the services offered by web
portals and information access and retrieval tools. With the rapid development
of biclustering, more researchers have applied the biclustering technique to
different fields in recent years. When biclustering approach is applied to the
web usage data it automatically captures the hidden browsing patterns from it
in the form of biclusters. In this work, swarm intelligent technique is
combined with biclustering approach to propose an algorithm called Binary
Particle Swarm Optimization (BPSO) based Biclustering for Web Usage Data. The
main objective of this algorithm is to retrieve the global optimal bicluster
from the web usage data. These biclusters contain relationships between web
users and web pages which are useful for the E-Commerce applications like web
advertising and marketing. Experiments are conducted on real dataset to prove
the efficiency of the proposed algorithms
Authentication of Students and Studentsâ Work in E-Learning : Report for the Development Bid of Academic Year 2010/11
Global e-learning market is projected to reach $107.3 billion by 2015 according to a new report by The Global Industry Analyst (Analyst 2010). The popularity and growth of the online programmes within the School of Computer Science obviously is in line with this projection. However, also on the rise are studentsâ dishonesty and cheating in the open and virtual environment of e-learning courses (Shepherd 2008). Institutions offering e-learning programmes are facing the challenges of deterring and detecting these misbehaviours by introducing security mechanisms to the current e-learning platforms. In particular, authenticating that a registered student indeed takes an online assessment, e.g., an exam or a coursework, is essential for the institutions to give the credit to the correct candidate. Authenticating a student is to ensure that a student is indeed who he says he is. Authenticating a studentâs work goes one step further to ensure that an authenticated student indeed does the submitted work himself. This report is to investigate and compare current possible techniques and solutions for authenticating distance learning student and/or their work remotely for the elearning programmes. The report also aims to recommend some solutions that fit with UH StudyNet platform.Submitted Versio
Image database system for glaucoma diagnosis support
Tato prĂĄce popisuje pĆehled standardnĂch a pokroÄilĂœch metod pouĆŸĂvanĂœch k diagnose glaukomu v rannĂ©m stĂĄdiu. Na zĂĄkladÄ teoretickĂœch poznatkĆŻ je implementovĂĄn internetovÄ orientovanĂœ informaÄnĂ systĂ©m pro oÄnĂ lĂ©kaĆe, kterĂœ mĂĄ tĆi hlavnĂ cĂle. PrvnĂm cĂlem je moĆŸnost sdĂlenĂ osobnĂch dat konkrĂ©tnĂho pacienta bez nutnosti posĂlat tato data internetem. DruhĂœm cĂlem je vytvoĆit ĂșÄet pacienta zaloĆŸenĂœ na kompletnĂm oÄnĂm vyĆĄetĆenĂ. PoslednĂm cĂlem je aplikovat algoritmus pro registraci intenzitnĂho a barevnĂ©ho fundus obrazu a na jeho zĂĄkladÄ vytvoĆit internetovÄ orientovanou tĆi-dimenzionĂĄlnĂ vizualizaci optickĂ©ho disku. Tato prĂĄce je souÄĂĄsti DAAD spoluprĂĄce mezi Ăstavem BiomedicĂnskĂ©ho InĆŸenĂœrstvĂ, VysokĂ©ho UÄenĂ TechnickĂ©ho v BrnÄ, OÄnĂ klinikou v Erlangenu a Ăstavem InformaÄnĂch TechnologiĂ, Friedrich-Alexander University, Erlangen-Nurnberg.This master thesis describes a conception of standard and advanced eye examination methods used for glaucoma diagnosis in its early stage. According to the theoretical knowledge, a web based information system for ophthalmologists with three main aims is implemented. The first aim is the possibility to share medical data of a concrete patient without sending his personal data through the Internet. The second aim is to create a patient account based on a complete eye examination procedure. The last aim is to improve the HRT diagnostic method with an image registration algorithm for the fundus and intensity images and create an optic nerve head web based 3D visualization. This master thesis is a part of project based on DAAD co-operation between Department of Biomedical Engineering, Brno University of Technology, Eye Clinic in Erlangen and Department of Computer Science, Friedrich-Alexander University, Erlangen-Nurnberg.
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
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