RapidMiner World2014

Similarity Assessment and

Resume Analysis using Clustering

and Cosine Similarity Measures in

RapidMiner

Surabhi Lodha

Santosh Vishwakarma

PROBLEM STATEMENT

• Every company’s main challenge is hiring of new individuals

• For recruitment the pool of resume a company gets for a job application is way larger than the number of people assigned to analyze it.

SOLUTION

• NEED OF TEXT MINING MODEL

• SORTING AND FILTERING OF KEYWORDS

• CATEGORISING OF RESUMES FOR BETTER PROCESSING

WHY RAPID MINER

• Rapidminer is an open source software package for predictive analysis.

• It is solid and complete package with flexible and affordable support options.

• Enterprise-ready performance and scalability for big data analytics Innovative analyst support.

• We can program by piping components together in a graphic ETL workflows.

• Rapidminer is very powerful due to its learning operators and operator framework, which allows to form nearly arbitrary processes

DATASET

• RESUMES OF GRADUATE STUDENTS OF VARIOUS STREAMS

– CSE 300

– CIVIL ENGG 225

– ELECTRICAL 200

– MECHANICAL 250

OUR APPROACH

PREPROCESSING OF RESUME DATASET

• TOKENISING

• STEMMING

• REMOVAL OF STOP WORDS

• INVERTED INDEX

PERFORM CLUSTERING USING K-MEANS

RESULT ANALYSIS

COMPARISONS BETWEEN CLUSTERS

COMPARISONS AMONG CLUSTERS

DATA SIMILARITY BW RESUMES

CONCLUSIONS

• Reduces the work of HR

• Project focuses on resume analysis by implementing clustering algorithm on resume dataset using rapid miner tool

• Selection of best resume in minimum time

THANKS