This post is a continuation of the previous post on Advertising on the Web and Data mining. Here we conclude by reviewing some basic algorithms for placing ads on the web.
Tag: data mining
The challenge of effective web advertisement primarily involves placing relevant ads on user requested web pages. Those ads must be relevant to a page receiver, that is relevant to the page context and/or directly to the user. What algorithms are being used for this? What trends are there now in business intelligence and data mining for digital advertisement solutions?
As we have touched on some basics on Clusters in Data Mining, we want to consider the computation techniques applied for clusters. Those techniques stand in line with the data mining for web traffic analysis.
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Clustering in Data Mining
Clustering is a data mining process where data are viewed as points in a multidimensional space. Points that are “close” in this space are assigned to the same cluster.
In Business Intelligence (and in data mining in general) a regular need is to be able to find the items that frequently go together in a consumer basket.
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Research Data Analysis of Web Traffic
I want to share on the research which was done by some Estonian students concerning web traffic analysis. The case study they undertook is about mining frequent user access patterns from web log files. The primary objective was to discover the most frequent browsing patterns by analyzing the browsing sessions in logs.
This short essay is about data mining methods applied in web traffic analysis and other business intelligence. It also provides a modern look at data mining in light of the Big Data era.
This short essay is about data mining methods applied in web traffic analysis and other business intelligence. It also provides a modern look at data mining in light of the Big Data era.
For a site owner, business blogger or e-commerce entity, there are always some variables of interest concerning web traffic and statistics. How would you predict future values of variables of interest? Variables of interest might include the number of visitors to a target website, the time each visitor spends on the site, and whether or not the visitor reaches the site’s goals. One needs to mention that these web traffic and site performance analyses are not imposed with stringent time constraints. Data mining techniques seek to identify relationships between the variable of interest and the variables in a data sample. There are at least 3 analysis models for data mining that we consider here.