Natural Language Processing is an aspect of artificial intelligence in which the computer program translates human language input by matching input characters or sounds with information in the knowledge base. The process of extracting data using text analytics has many applications, including translating text from one language to another, voice recognition software, and text-to-voice applications. The combination of natural language processing (NLP), business intelligence, and data mining, is the basis of the success of the largest and most successful search engine, Google.
Natural Language Processing For Text Data Mining
Google uses natural language processing to enhance a user’s search results. It is seldom that a search string of text can be matched exactly to an online source. For example, individuals typing the text string, “Google search results are stored for years” will not commonly find an article or website with the exact words they were searching for. Instead, Google’s NLP algorithms interpret the text string to determine what the consumer is really looking for. Google then returns search results that reflect that meaning. In addition, Google checks for typos and spelling mistakes, to ensure that users get the best possible results, as evidenced by their “Did you mean” feature.
Data Mining Technology Applications
Data mining technology is an extremely useful aspect of business intelligence applications. Data mining software uses information to see patterns in past behavior, buying, selling, movement, traffic, or any other aspect of business. Patterns in shopping behaviors, for example, tell shop-owners where to place certain types of products. The patterns identified by data mining applications can then be used to identify trends, and make future predictions. Google, Inc. currently uses a combination of data mining technology and NLP to improve advertising revenue.
Google’s Business Intelligence Solutions
Google stores the information from every search, and associates it with the user account or computer used for the search for up to 18 months. Data mining techniques are used to determine shopping habits, personal interests, and other information that allows for targeted marketing directly to an individual’s needs. The advertisements and search results are increasingly customized as additional information is acquired by Google.
Benefits of Data Mining in Business Intelligence
As Google increases the amount of information stored, the data extracted through data mining and text analytics can offer better services to advertisers. The more customized advertisements are, the more likely it is that a consumer will click on an ad (increasing revenue for Google) and purchase the product (increasing revenue for the advertiser). Consumers also benefit, since they are more likely to find the products they are looking for. In addition, evaluating search trends allows Google to provide better information on the spread of the Swine Flu than even the CDC could provide.
As Google, Inc. continues to gain market share, it also gathers increasing amounts of information. Google’s databases contain a vast storehouse of information about consumers around the world, from products purchased, to search history, and even personal financial information. Sophisticated NLP algorithms, combined with text analytics and data mining techniques, produce benefits to consumers, businesses, and society as a whole.
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