Data Sources, Use Cases and Capabilities

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Presentation transcript:

Data Sources, Use Cases and Capabilities Text Mining: Data Sources, Use Cases and Capabilities Kayvis Damptey Jie Zhang Dec 8, 2016

What is Text Mining?

Text Mining Text Mining uses documents to identify insightful patterns within the text. Thus allowing managers to summarize/organize huge collections of documents and automate detection based on useful linguistic patterns. Detecting these patterns can be done via the following methods: Keyword/Event Detection Word Clouds Visualizations Natural Language Processing Topic Discovery/Category Assignment Sentiment Analysis Financial Management Services November 13, 2018

What skills are needed to do Text Mining? Understand Linguistic Nuances Domain Knowledge Probability and Linear Algebra Computer Programming Financial Management Services November 13, 2018

Past Use Case: Business Problem: Remedy Topic Discovery With many tickets coming into Financial Support Center, there was a need to understand what general topics were being discussed in many of the tickets to better understand which issue need to be resolved faster or had the most tickets. Financial Management Services November 13, 2018

Past Use Cases: Remedy Topic Discovery Approach: Data Cleansing: Curate data for modeling, including relevant customer data, and keywords in the text, spell checking etc. Filter data based on things like excessive symbols (and thus maybe just a long email exchange) Standardize slang/abbreviations and clean the text from spelling errors Data Transformation: By creating a “ticket by term” matrix the tickets can be scored based on their term-frequency combinations (which is an approximation of the antonyms and synonyms). Modeling and Scoring: The tickets are then grouped based on the proportion of the co-occurrence of their term-frequency combination score. Financial Management Services November 13, 2018

Past Use Cases: Remedy Topic Discovery from 1,168 tickets Solution: Financial Management Services November 13, 2018

Everyday Textmining

How might text mining be useful in everyday situations? Automatic Categorization and response to incoming documents Detect strong customer sentiment towards a product or service Discovering Common Topics of many documents Summarizing documents Detecting comments about actions taken by key partners Extract location information from descriptions Financial Management Services November 13, 2018

Jie Zhang (jzhang28@Stanford.edu) Kayvis Damptey (kayvis@Stanford.edu)