Hansheng Lei Univ. of Texas Rio Grande Valley

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Presentation transcript:

Hansheng Lei Univ. of Texas Rio Grande Valley Data Intelligence Hansheng Lei Univ. of Texas Rio Grande Valley

Outline Artificial Intelligence (AI) vs. Data Intelligence (DI) DI Examples Mining Dependent Patterns Discovering Multiple Relations Predict Prices Summary ICDIS 2019 – The 2nd Int. Conf. on Data Intelligence and Security

AI a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving" Artificial intelligence: Google's AlphaGo beats Go master Lee Se-dol, March 12, 2016

AI Since the beginning of Computer

Data Intelligence Combination of AI and machine learning (ML) Descriptive: For reviewing and examining the data to understand and analyze business performance. Prescriptive: For developing and analyzing alternative knowledge that can be applied in the courses of action Diagnostic: For determining the possible causes of particulate occurrences. Predictive: For analyzing historical data to determine future occurrences. Decisive: For measuring the data adequacy and recommending future actions to be undertaken in an environment of multiple possibilities.

DI Picture source: https://www.quora.com/What-is-data-intelligence

Association Rule Mining Proposed by Agrawal et al in 1993. Applied in market basket analysis to find how items purchased by customers are related. Beer  Diaper [sup = 5%, conf = 100%]

Association rules An association rule is an implication of the form: X  Y, where X, Y  I, and X Y =  An itemset is a set of items. E.g., X = {milk, bread, cereal} is an itemset.

Problems with AR mining generates a huge amount of rules Not supporting other relations, such as negative implication, correlation and dependence Universal support and confidence

Dependent Patterns

DP Properties Downward closure Individual support thresholds for each item Right dependence measure

Pattern Distribution

Discovering Multiple Relations In traditional statists, multiple regression is often used find the relations between a set of variables and a single dependent variable. 𝑦= 𝛼 1 𝑥 1 +𝛼 2 𝑥 2 +… +𝛼 𝑛 𝑥 𝑛 +𝜖

Discovering Multiple Relations Top ten functions from output sorted by SSR (sum of squared residuals).

Predicting Prices

Predicting Prices Average Price by Description Length Mean Price by Main Category Average Price by Description Length

ICDIS 2019 Volunteers wanted!