ANNOTATING WEB SEARCH RESULTS
Need help with a related project topic or New topic? Send Us Your Topic
DOWNLOAD THE COMPLETE PROJECT MATERIAL
ANNOTATING WEB SEARCH RESULTS
Chapter One: Introduction.
People from various walks of life use the internet for a variety of purposes, including buying and selling, social networking, digital libraries, and news.
Researchers require information from digital libraries and other online document repositories to conduct their research and share information; scholars require books to obtain information and knowledge;
people communicate with one another via email; others use social media to exchange information and have casual chat; and some conduct transactions such as purchasing items and paying bills via the internet.
The World Wide Web is now the primary storehouse for “all kinds of information” and has shown to be extremely effective in transmitting information to people.
Many database applications, including e-commerce and digital libraries, now use the Web as their primary media. Many database applications store information in massive databases that users may access, query, and update via the Web.
Improvements in hardware technology have resulted in increased storage capacity for PCs and servers. As a result, many web servers store a large amount of data on their storage systems.
Some social networking platforms, such as Facebook[1], allow users to submit photos, videos, and other documents. YouTube [2] allows users to upload films of various durations to its servers.
Other automatic systems acquire large amounts of data on a daily basis. Bank systems, for example, must keep both daily ATM transactions and those of other clients.
Some monitoring systems collect data on certain aspects of life, such as climate change, while others maintain track of their customers’ regular purchasing experiences. These are only a few examples of how a massive amount of information and papers have become available on the Internet.
However, due to the variety and lack of organisation of Web information sources, access to this vast collection of data has been restricted to browsing and searching. That is, to access a document, enter the URL (Universal Resource Locator) into a Web Browser or utilise a search engine.
The former method is appropriate when you know exactly what you’re looking for and where to find it on the internet. However, this is not the case, and as a result, many Web users use search engines to find specific content.
There are software systems that need a user to manually enter a search phrase, after which the search engine collects documents based on the query; however, there are also automated search engines that use a Web Crawler.
There are numerous significant web-based search engines that index web documents and are accessible to Web users. Google, Yahoo, AltaVista, and numerous more are among the most popular.
Such systems search through a collection of materials sourced from both the Surface Web, which is indexed by regular search engines, and the Deep Web, which requires specialised tools to reach.
Most consumers profit from such systems when they are looking for unknown information or need to reroute to a website they know but cannot remember the URL of.
However, some business disciplines, such as Competitive Intelligence [3], require a specific sort of information (domain-specific) in order to make strategic business decisions. In such cases, several tools are developed to aid in information gathering and processing.
Several alternative approaches for searching and retrieving information to acquire intelligence are also applicable in these domain-specific domains.
For example, manually perusing the Internet could be the simplest way to do a Competitive Intelligence work. Manual Internet browsing at a suitable level ensures the quality of documents collected, which improves the quality of knowledge that may be discovered.[4]
However, the difficulty here is that a significant amount of time is invested. According to Onu, a survey of over 300 Competitive Intelligence specialists found that data gathering is the most time-consuming task in typical Competitive Intelligence projects, accounting for more than 30% of overall project time.
In this instance, it is cognitively tiring and burdensome for Competitive Intelligence professionals to manually search the Internet, reading the content on each page of a Website in order to discover important information and synthesise the information.
Need help with a related project topic or New topic? Send Us Your Topic