Page 177 - DCAP208_Management Support Systems

Management Support Systems

Notes Self Assessment

State True or False:
11. Text mining is more difficult for computers to do.
12. A process called data mining is different from the mining of text.

10.4 Web Mining

Web mining is a form of information harvesting that applies to data gathered from online
sources. Data collection from sources across the Internet allows users to aggregate large volumes
of information for analysis to make key business decisions in an online environment.

Example: A researcher might use web mining to collect information regarding the use
of specific keywords in web content.
Alternatively, retailers and other marketing professionals use online data mining to spot trends
in web traffic, the conversion of site visitors to buyers, and other web usage.
In terms of gathering, sorting, and analyzing data, web mining mimics traditional data mining
activities. Comparatively, web mining activities focus on web-based information, rather than a
large cross section of information sources such as off-line computer databases, customer records,
or hard copy accounting data, as typically occurs with traditional data mining. Focusing solely
on data collection from online sources provides targeted analysis needed for online marketing
strategies, website structure decisions, and similar electronic commerce-related decision making.
Collecting data via web mining also provides the added benefit of a broad international
demographic, since websites from all over the world are available to researchers and information
gatherers.
Professionally, web mining is divided into three specific categories: web structure mining,
usage mining, and web content mining. Each area focuses on specific information such as the
structure and hyperlinks of a particular website, server log information regarding visitor usage,
and specific content available online.
Website analytic software packages and services are a prime example of web usage mining,
providing webmasters with information regarding visitor traffic, search results used, links
clicked, and time spent interacting with specific pages. Structure mining, on the other hand,
provides detailed information about a specific website’s internal structure, including hyperlinks,
databases, and query functions.
To the marketing professional, web mining offers a wealth of uses relative to marketing activities.
Knowing how site visitors use a particular website, how competitors set up a competing site,
and what content is already online is valuable information. Such information helps key decision
makers craft a marketing strategy based on previously proven techniques and documented
information.
Colleges and universities also utilize web mining via software that verifies student papers are
unique and not plagiarized. Using web content mining principles, such grading aides search the
entirety of the Internet for like content. Instructors upload the text of a student document and
then instruct the plagiarism software to check the Internet for similar phrases or copied text
online. Results are often expressed as percentage of matching text. Links to any similar results
are provided to allow instructors the ability to visit sites to determine if matches are indeed
plagiarized.

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