Monthly Challenge – Ontotext case – Solution – Team epistemi

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Week 1. Data Understanding + Feature Extraction We have been provided with a dataset consisting of 277419 records, which are extracted from DBpedia. It has 6 features and 1 label of 32 classes as summarised in below table: ID Item Name Item Type Observations 1 org Feature URL; may be useful for extraction of additional […]

Monthly Challenge – Ontotext case – Solution – Door

Posted 4 CommentsPosted in Classification systems

1. Business Understanding¶ Developing an automated and standardized classification model that can be used on any source to enrich the originally available data with industry sector information. Ultimately the task can be framed as an error/anomaly detection task. At the core, it is still a classification problem and the output should be not the ultimate […]

Monthly Challenge – Ontotext – Case

Posted Leave a commentPosted in Cases, Learn, MC-04-2019

Monthly Challenge: https://www.datasciencesociety.net/events/text-mining-data-science-monthly-challenge/ Mentors’ Weekly Instructions: https://www.datasciencesociety.net/text-mining-data-science-monthly-challenge/ Real Business Problem Classification of companies into industry sectors is a fundamental task for unlocking advanced business intelligence capabilities. However different data sources rarely use the same classification system if any. This is a huge obstacle for taking advantage of the available details in Open Data and very niche commercial […]

Text Mining Data Science Monthly Challenge

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Why you should join the Data Science Monthly Challenge and what you can expect? The Data Science Monthly Challenge provides an exceptional opportunity for participants, no matter of their background and previous experience, to be involved in finding a solution to a real data science problem step by step. The proposed gradual approach towards advanced business […]