Obi Ogbanufe Popular Books

Obi Ogbanufe Biography & Facts

Click tracking is when user click behavior or user navigational behavior is collected in order to derive insights and fingerprint users. Click behavior is commonly tracked using server logs which encompass click paths and clicked URLs (Uniform Resource Locator). This log is often presented in a standard format including information like the hostname, date, and username. However, as technology develops, new software allows for in depth analysis of user click behavior using hypervideo tools. Given that the internet can be considered a risky environment, research strives to understand why users click certain links and not others. Research has also been conducted to explore the user experience of privacy with making user personal identification information individually anonymized and improving how data collection consent forms are written and structured. Click tracking is relevant in several industries including Human-Computer Interaction (HCI), software engineering, and advertising. Email tracking, link tracking, web analytics, and user research are also related concepts and applications of click tracking. A common utilization of click data from click tracking is to improve results' positions from search engines to make their order more relevant to users' needs. Click tracking employs many modern techniques such as machine learning and data mining. Tracking and recording technology Tracking and recording technologies (TRTs) can be split into two categories, institutional TRTs and end-user TRTs. Institutional TRTs and end-user TRTs differ by who is collecting and storing the data, and this can be respectively understood as institutions and users. Examples of TRTs include radio frequency identification (RFID), credit cards, and store video cameras. Research suggests that individuals are concerned with privacy, but they are less concerned with how TRTs are used daily. This discrepancy has been attributed to the public not understanding how information about them is getting collected. Another means of obtaining user input is eye-tracking or gaze tracking. Gaze-tracking technology is especially beneficial for those with motor disabilities. Systems that employ gaze-tracking often try to mimic cursor and keyboard behavior. In this process, the gaze-tracking system is separated into its own panel in the system interface, and the user experience of this system is compromised as individuals have to switch between the panel and the other interface features. The experience is also difficult because users have to first imagine how to complete the task using keyboard and cursor features and then employ gaze. This causes tasks to take additional time. Hence, researchers created their own web browser called GazeTheWeb (GTW), and the focus of their research was on the user experience. They improved the interface to incorporate gaze better. Eye-movement tracking is also applied in usability testing when creating web applications. However, in order to track user eye movements, a lab setting with appropriate equipment is often required. Mouse and keyboard activity can be measured remotely, so this quality can be capitalized for usability testing. Algorithms can use mouse movements to predict and trace user eye movements. Such tracking in a remote environment is denoted as a remote logging technique. Browser fingerprinting is another means of identifying users and tracking them. In this process, information about a user is collected from their web browser to create a browser fingerprint. A browser fingerprint contains information about a device, its operating system, its browser, and its configuration. HTTP headers, JavaScript, and browser plugins can be used to build a fingerprint. Browser fingerprints can change over time from automatic software updates or user browser preference adjustments. Measures to increase privacy in this realm can reduce functionality by blocking features. Methods of click tracking User browsing behavior is often tracked using server access logs which contain patterns of clicked URLs, queries, and paths. However, more modern tracking software utilizes JavaScript in order to track cursor behavior. The collected mouse data can be used to create videos, allowing for user behavior to be replayed and easily analyzed. Hypermedia is used to create such visualizations that allow for behavior like highlighting, hesitating, and selecting to be monitored. Technology that is used to record such behavior can also be used to predict it. One of these monitoring tools, SMT2є, collects fifteen cursor features and uses the other fourteen to predict the last feature's outcome. This software also generates a log analysis which summarizes user cursor activity. In a search session, users can be identified using cookies, identd protocol, or their IP address. This information can then be stored in a database, and every time a user visits a web page again, their click behavior will be appended to the database. DoubleClick Inc. is an example of a company that has such a database and partners with other companies to aid with their web mining. Cookies are added to HTTP (Hypertext Transfer Protocol), and when a user clicks on a link, they are connected to the associated web server. This action of a user clicking on a link is seen as a request, and the server “responds” by sending the user's information, and this information is a cookie. Cookies provide a “bookmark” for users’ sessions on a website, and they store user login information and the pages users visit on a website. This aids with preserving the state of the session. If there is more than one such server, information must be consistent among all servers; hence, information is transferred. Data collected via cookies can be used to improve websites for all users and this also aids with user profiling for advertising. When data mining techniques and statistical procedures are applied to understand web log data, the process is noted as log analysis or web usage mining. This helps with determining patterns in the users’ navigational behaviors. Some features that can be observed include how long users viewed pages for, click path lengths, and the number of clicks. Web usage mining has three phases. First, the log data is "preprocessed" to see the users and search sessions’ content. Then, tools like association and clustering are applied to look for patterns, and lastly, these patterns are saved to be further analyzed. The tool of association rule mining helps with finding “patterns, associations, and correlations” among pages users visit in a search session. Sequential pattern discovery is association rule mining, but it also accounts for time like the page views in an allotted time period. Classification is a tool that allows for pages to be added to groups representing certain similar qualities. Some examples of tools individuals can use when conducting click analytics are the Google Analytics tool In-Page Analytics, ClickHeat, and.... Discover the Obi Ogbanufe popular books. Find the top 100 most popular Obi Ogbanufe books.