For the past few months, a “very large fraction” of the millions of queries a second that people type into the company’s search engine have been interpreted by an artificial intelligence system, nicknamed RankBrain, said Greg Corrado, a senior research scientist with the company, outlining for the first time the emerging role of AI in search. RankBrain uses artificial intelligence to embed vast amounts of written language into mathematical entities — called vectors — that the computer can understand. If RankBrain sees a word or phrase it isn’t familiar with, the machine can make a guess as to what words or phrases might have a similar meaning and filter the result accordingly, making it more effective at handling never-before-seen search queries. READ MORE: Google Turning Its Lucrative Web Search Over to AI Machines | Bloomberg
Text-mining programs go further, categorizing information, making links between otherwise unconnected documents and providing visual maps via What is Text Mining? | Information Space.
Text mining, or the indexing of content, is important because it allows us to make sense and extract meaning out of large amounts of data. Text-mining is an activity also related to data curation, the semantic web, big data and bioinformatics. Its becoming more popular as a way to conduct research and information retrieval within databases.
Here is an informative presentation called The Library as Dataset: Text Mining at Million-Book Scale from Yale University, which discusses a text mining method, digital humanities and libraries.
Here is an article with an information science perspective called Text Mining and Information Retrieval, Canadian Journal of Information and Library Science, 2011, 35(3), pp. 223-227, if you have access to scholarly databases.