IMAGE MINING Image Mining is an extended branch of data mining that is concerned with the process of knowledge discovery from images. Image mining deals with the extraction of image patterns from a large collection of images. It can be done manually by slicing and dicing the data until a pattern becomes obvious. Or, it can be done with programs that analyze the data automatically. Color, texture and shape of an image have been primitive image descriptors in Content Based Image Retrieval (CBIR) system.
The basic concept is to extract coherent blocks of text from HTML pages, using DOM parsing, and to compute linguistic and structural features for each block. These features are then forwarded to classiers that decide whether to keep or discard the block at hand. To this end, we use diverse popular classication models for learning feature thresholds.FastContentExtractor - a fast algorithm to automatically detect content blocks in web pages by improving ContentExtractor. Instead of storing all input web pages of a website, Son Bao Pham and teammates have automatically created a template to store information of
Detecting outliers and analyzing large data sets can lead to discovery of unexpected knowledge in area such as fraud detection, telecommunication, web logs, and web document, etc. This paper focuses to clarify the problem with detecting outlier over data stream and specific techniques used for detecting outlier over streaming data in data mining.
Search engine developers are always striving to deliver search results that are relevant to the search query being processed. Consistent with this goal, there have been attempts to rank search results based on a number of different factors. One of the more popular ways to rank search results involves analyzing the location and frequency of keywords on a web page. Another frequently used technique is analyzing how web pages link to each other. A web page gets a ranking boost based on the number of other web pages that are linked to it.
Any Java applet creation tool can be employed in WordPress templates. These tools can then be made to create various avenues of providing context sensitive help. The tools allow both the creation of on page help as well as creating a knowledge base that can support the definitions employed in the context sensitive help pop-ups and tooltips. The Importance of Context Sensitive Help Context sensitive help is extremely important for creating a well established website that aims to promote its ideas clearly. Context sensitive help allows users to fully understand the different terms described on a webpage.
This is different from client side scripting however, since to be a server side script the data must be executed on the web server side, compared to the Client side scripts which are executed by the user’s browser. Different Web Server Scripting Languages: There are many different server side scripting languages which can be used on the web servers, these include: ASP: This is Microsoft’s web server scripting product which will commonly only run on a Windows based server. Files have the file extension of .asp which stands for Active Server Pages. Finally VBScript are used within ASP pages. ASP.net: ASP.NET is an open-source server-side web application framework designed for web development to produce dynamic web
Association Rule Learning (Dependency modeling) is a method that describes associated features in data, searching for relationships between variables. As an example, Web pages that are accessed together can be identified by association analysis. Anomaly Detection (Outlier/change/deviation detection), this class identifies anomalies or outlier data records which cause errors, or might be of interest and requires further investigation. Another class is Clustering, which is the task to discover groups and structures in the data which in some aspect is “similar” or “dissimilar”, without using known structures in the data And the last class, Summarization, attempts to provide a more compact representation of the data set, including visualization and report
Van Deursen and van Dijk (2014) resume this perspective, but stating that the great diversity of definitions makes it difficult to have a clear characterization of digital skills. Therefore, they propose a definition of digital skills, both conceptual and operational, in four sequential domains: Operational, formal, information and strategic. The authors understand by operational skills the actions that allow a person to use digital media tools, such as navigation bars, buttons or links, different ways to input information in fields or pages, possibilities to download or save files and similar. As for the formal skills, they refer to navigation and orientation in structures specific to digital media (in essence, hypertextual), such as knowing which website one is in, identifying how to navigate each site, orienting oneself or getting lost while performing a task. The information skills are related to knowing how to search, select and assess the information from internet in its various forms (text, image, video).