Is Mining Search Keywords Some Kind of Data Mining Task?

Recently I noticed there are many keyword research tools are available in digital marketplace which help to identify niche keywords for promoting or advertising of specific product. Some businesses also lately eager to find search keywords which are relevant to their product or service promotion. Among other reason is because optimizing search keywords is critical to get a higher ranking in the current search engines. In term of data mining task, the data source here are the biggest on-line database (WWW), specifically search keywords of the available search engines.

Before we start, let me explain why search keywords are important to many search engines. For example, Google’s seach engine does the work for you by searching out Web pages that contain the keywords you used to search, then assigning a rank to each page based on several factors, including how many times the keywords appear on the page. Higher ranked pages appear further up in Google’s search engine results page (SERP), meaning that the best links relating to your search query are theoretically the first ones Google lists.

According to the Microsoft adCenter Labs, keyword research technology goes beyond traditional data mining because of the scale and scarcity of the data. For example, in the study of keyword semantics alone, there are many potential relationships such as synonymy, antonymy, similarity, membership, attribute, causation, hierarchy, and substance. Tools in the Keyword Research category exploit such relationships between the keywords.

We know that data mining tasks include classification, association rules, dependence modeling etc. Well, I can say that at least research keyword tools are belong to association rules task because this data mining tool provides a graphic view of the associations between entities by mining the co-occurrences of entities in search queries or search sessions. Such associations will be useful when creating query suggestions or analyzing user search patterns.

I have managed to try one keyword research tool available in the market called Keyword Research Pro. Keyword Research Pro pulls keywords from the biggest databases online, adding up to several million keywords. No other keyword tool is able to pull keywords from so many different keyword sources. In addition, it has a built-in ‘auto-digging’ feature that will dig down multiple layers of keywords to return to you the desired number of keywords you require. So for example, if you require 1,000 keywords for ‘weight loss’, Keyword Research Pro will fetch keywords and ‘auto dig’ until it returns you 1,000 ‘weight loss’ related keywords. Keyword data sources include:

– Google AdWords Keyword Tool
– Keyword Discovery
– Wordtracker
– 7Search
– Miva
– YouTube
Keyword Research Pro will not only tell you how popular any keyword is, it will also tell you how much competition there is, how many people are advertising on those keywords, how much they are paying, their actual ad copy, you can even view your competitors actual landing pages!

Keyword Research Pro Analysis Options:
– Competition: Google, Yahoo & Bing (Phrase or Broad Match, AllInTitle (default) & AllInAnchor)
– Search Volume: Google (default), Wordtracker, 7 Search, Keyword Discovery
– Keyword Effectiveness: Keyword Effectiveness Index (default) & R/S Ratio
– Pay-Per-Click Info: Average Cost-Per-Click (Broad, Phrase, Exact) and Competing Ads (Analyze competitors’ PPC ad copy and actual landing pages with ease!)

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Video Compilation of Practical Data Mining Techniques

Nowadays, it is very difficult for new data mining beginner to watch free video tutorial of data mining techniques in a single place. Because of that reason, I have created new page in my site to showcase video compilation of practical data mining techniques using known software/tools available in the market today. The compilation videos are categorized into data mining techniques, which are classification; clustering; regression; neural network etc. I will try to update the list every week if new video is available in the web. If you know other sources of video tutorial using different software/tools not listed here then feel free to add in the comment section.
For an Overview of Data Mining Techniques, visit here.

1. Classification
Software: Rapidminer 5.0
This video shows how to import training and prediction data, add a classification learner, and apply the model.
Application: building a Gold Classification trend model.

Software: Rapidminer 5.0
This video shows how to use Rapidminer to create a decision tree to help us find “sweet spots” in a particular market segment. This video tutorial uses the Rapidminer direct mail marketing data generator and a split validation operator to build the decision tree.
Application: creating Decision Trees for Market Segmentation.

This video shows how to use CHAID decision trees to classify good and bad credit risk. CHAID decision trees are particularly well suited for large data sets and often find application in marketing segmentation. This session discusses the analysis options in STATISTICA and review CHAID output including the decision trees and performance indices.

2. Clustering
This video shows how to use clustering tools available in STATISTICA Data Miner and demonstrates the K-means clustering tool as well as the Kohonen network clustering tool.
Application: Clustering tools are beneficial when you want to find structure or clusters in data, but dont necessarily have a target variable. Clustering is used often in marketing research applications as well as many others.

Software: WEKA
This video shows how to use clustering algorithm available in WEKA and demonstrates the K-means clustering tool.
Application: building cluster model of bank customer based on mortgage application.

3. Neural Networks (NN)
– Neural Networks is a sophisticated modeling tool, capable of modeling very complex relationships in data.
Software: WEKA
This video shows how to use neural network functions available in WEKA to classify real weather data.
Application: building weather prediction model

4. Regression

This video explores the application of neural networks in a regression problem using STATISITCA Automated Neural Networks. The options used for regression are similar for other neural networks applications such as classification and time series. The episode explores various analysis options and demonstrates working with neural network output.

This video uses the regression data, beverage manufacturing, to explore C&RT as well as the other tree algorithms. The options and parameters are reviewed as well as important output.

5. Evolutionary/Genetic Algorithms
Software: Rapidminer 5.0
This video highlights the data generation capabilities for Rapidminer 5.0 if you want to tinker around, and how to use a Genetic Optimization data pre-processor within a nested nested experiment.

Software: Rapidminer 5.0
This video discusses some of the parameters that are available in the Genetic Algorithm data transformers to select the best attributes in the data set. We also replace the first operator with another Genetic Algorithm data transformer that allows us to manipulate population size, mutation rate, and change the selection schemes (tournament, roulette, etc).

Software: Rapidminer 5.0
This tutorial highlights Rapidminer’s weighting operator using an evolutionary approach. We use financial data to preweight inputs before we feed them into a neural network model to try to better classify a gold trend.

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Data Mining Search and Twitter Trend in 3D

Following to my previous post titled “Data Mining In Different Views“, I would like to add one more view to the current views of Data Mining information from web search engine. Using Tianamo browser-based 3D information visualization interface, we can view data mining search results from Yahoo search engine in 3D. You can view the latest 3D results on “Data Mining” by clicking the image below, but I need to remind that your browser must have Java Runtime Environment (JRE) installed in your machine. The advantage of viewing 3D search results is that you can identify what are the main keywords for the topic you are searching just by looking at which keyword has the “highest mountain” in the overall 3D view. For instance, in the current view, the main data mining search results keyword is “report”.

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