(PDF) Text Mining Business Intelligence
Added on 2021-06-18
13 Pages2719 Words119 Views
Data Science and Big DataArtificial Intelligence
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InstitutionStudent NameBusiness Intelligence
TEXT MININGText mining is the process of mining or deriving information of high quality from text [ CITATION Cou08 \l 1033 ]. Such information is arrived at by devising trends and patterns through means likestatistical pattern learning. In text mining, high quality refers to a combination of novelty or relevance. Text mining tasks include sentiment analysis and document summarization. Data mining however is the process of obtaining patterns in data sets[ CITATION Han11 \l 1033 ]. Overall goal of this is to extract relevant information from a dataset and transform it into a structure that is understandable.Data mining is a general process that includes text mining. However, data mining is the extraction of relationships from structured data e.g., pie charts or tables whereas text mining involves extraction of insights from a dataset. Text retrieval processes range from a preparatory step to the final step of compiling the high-quality information.Information retrieval involves identifying and collecting a corpus in a database for analysis[ CITATION Pan02 \l 1033 ]. Text analytic systems apply natural language processing e.g., syntactic parsing and other forms of linguistic analysis.Named entity recognition involves statistical techniques, gazetteers etc. for identifying named text features; abbreviations and stock ticker symbols [ CITATION JRQ96 \l 1033 ].Disambiguation involves use of clues that are contextual.Recognition of Pattern Entities involves features like email addresses, telephone numbers, which are discerned through regular expression or other kinds of pattern matching.Text mining also involves co-referencing, the identification of terms that refer to a similar object.This is followed by Fact, Relationship or Event Extraction through which associations among entities in a text is identified.Sentiment analysis encompasses discernment of subjective material and extraction of various levels of attitudinal information: mood, sentiment etc.[ CITATION MKu13 \l 1033 ].Quantitative text analysis involves techniques like social sciences, where either a computer or a human judge/analyst extracts semantic relationships between text-data so as to find out the stylistic patterns, meaning of a casual text that may be personal for the aim of psychological profiling [ CITATION JRQ96 \l 1033 ].
Text mining is applied for a variety of research, business or government needs [ CITATION SBK07 \l1033 ]. Application categories include E-discovery and Enterprise Business Management.
ARTIFICIAL INTELLIGENCE1.Why artificial Intelligence is important for supporting business to build smart systems.Artificial intelligence is slowly changing the course of engineering in this century. Accuracy and precision of artificial intelligence based systems has made companies make unimaginable returnson investment[ CITATION For18 \l 1033 ]. Artificial systems are reliable and not subject to bias as inhumans hence facts and figures presented using these software is the truth.2.How artificial intelligence helps to transform companies HANA analyses transaction data for trends. When used with supportive applications, decision making is faster. Operational costs are saved enormously as anomalies in sales that could cause losses is identified and appropriate resolution suggestions made. AIs make data-driven decisionswhich are better informed. Walmart uses this software in its excess of 11,000 stores to monitor transactions in real time [ CITATION Men11 \l 1033 ]. A report sponsored by SAP gives a revelation, that companies incorporating their cloud platform,HANA, expect an investment return higher than 575%.Domo, another cloud based platform collects data from third-party platforms like Facebook, Square, and uses that data to give insights and provide context to intelligence. By monitoring the performance of the product at sales points, this AI spots rising trends in real-time and generates reports on these trends, offering suggestions on action to take for improvement.Apptus another AI, interestingly learns patterns of customers and enables them to purchase products by automatically giving them suggestions on the products they search. It also recommends actions to be taken to boost sales after analyzing the consumers’ preferences for related products. Working using the same principle of predictive analytics is Avanade which is a joint venture by Accenture and Microsoft leveraging on Cortana Intelligence Suite for data-basedinsights [ CITATION Wit11 \l 1033 ].General Electric’s Predix, working with industrial applications, processes historic performance information of equipment and uses this data to predict operational outcomes i.e., when equipment may fail. It still uses the principle of predictive analytics. By calculating the time an equipment can work before maintenance and giving alerts on maintenance [ CITATION Pan02 \l 1033 ]. Siemens’ MindSphere like Predix monitors fleets of machines for service needs using drive train analytics. Unlike Predix, it can work with machines from any manufacturer.
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