PERSONALIZED JOB MATCHINGMd. Mustafizur RahmanEllie CloughertyJohn CloughertySam Hewitt

OUTLINE

Introduction Existing System Existing Work (Research) Lacking of existing systems Format of Job and Resume Our Approach System Component Evaluation Job Analytics Future Works

JOB MATCHING

A search engine that takes user input (i.e. job title, company name, qualification etc.) and suggests him/her the recommended job.

User input Resume Job Postings Keyword

EXISTING SYSTEM

There are multiple job searching websites like Glassdoor Monster Indeed

But very few support for resume searching Indeed

EXISTING SYSTEM

EXISTING SYSTEM

EXISTING SYSTEMS

EXISTING SYSTEM

EXISTING WORK (RESEARCH)

Collaborative filtering [1] Critically dependant on the availability of high-

quality user profiles Quite rare in the real world scenario

Content based filtering [2] Highly dependent on user interaction

LACKING FEATURES

Absence of personalization No support for user preference (i.e. New job

seekers tend to put more on their educational qualification than experience in a resume)

Absence of resume and job dynamics Keyword/term correlated experience and

expertise searching.

There is no way to search for a job using your entire skill set and experience

SOLUTION

● Personalized Job Matching System○ Crawl resume○ Compare against a continuously-growing

database of job-postings across multiple sites and companies

○ SQL commands to explore the nature of the data and find patterns

● Prototype an Economic Job Graph

JOB POSTING: GOOGLE JOB

RESUME: INDEED.COM

Job Posting Resume

Job Title Title

Qualification

Responsibilities

Job Description

Educational Background

Experience

Additional Information

TYPICAL FORMAT OF JOB POSTINGS AND RESUME

FIELD TO SEARCH FOR

Job Posting Resume

Job Title Title

Qualification

Responsibilities

Job Description

Educational Background

Experience

Additional Information

OUR APPROACH: KEY FEATURES

A specialized search engine

Full text resume and job search

User control over the field

Aspect based (keyword based) experience

correlation

Job prediction

OUR APPROACH : SYSTEM COMPONENTS

As a specialized search engine we have the following components

Crawler Doc Analyzer Indexer Ranker Interface Evaluation

CRAWLER (COLLECTION OF DATA)

Problem No benchmark job postings data set No benchmark resume data set Scarce resource of resume!

Solution Crawler

We have to build specialized crawler for different employer and resume websites

3 different crawler for job posting: Google, Facebook and IBM

1 crawler for resume: indeed.com

DOC ANALYZER

Lets take a look in job postings :

BA/BS -> Bachelor of Arts/ScienceMS - > Master of ScienceSolution: Dictionary Expansion

Unix/LinuxData StructureAlgorithmSoftware designObject oriented skillsJavascriptNetwork programming

How to identify these?

DOC ANALYZER (CONTD.) Problem: Can we identify the keywords from

the open unstructured text?

Solution 1: Unigram model Problem: keywords: Software Design

becomes Software -> less important than Software

Design Design -> less important than Software

Design

Solution 2: Phrase Query Problem: How to make phrase query

when your input is a complete resume?

DOC ANALYZER (CONTD.)

Our observation: Most of these keywords are Noun Most of these keyword appears only after some

preposition (in, with) For multiple word keyword (i.e. Software Design) search for consecutive Noun. Use of Parts of Speech Tagger

Results are quite fascinating, we have got most of the meaningfull keywords.

DOC ANALYZER (CONTD.)

Take a look again on a job postings

Question: Suppose you have all the qualifications, but not 4 years of experience, where should a job search engine rank this result?

DOC ANALYZER (CONTD.) Can we indentify keywords oriented experience

list for a job postings (or resume) like below?

We already have the keywords list!!. Just simply find out the year of experience using the parts of speech tagger and some heuristics.

Keywords Experience

C++, Java 2 years

Software Development 5 years

TCP/IP Not necessary

…. …

INDEXER

Two indexers Job Posting Resume

Job Posting Indexer Job Title Job Location Job Qualification Job responsibilities Job keywords (Processed from Data Analyzer) Job experience (Processed from Data Analyzer)

INDEXER (CONTD)

Two indexer Job Posting Resume

Resume Indexer Resume Title Educational Information Experience Additional information Resume keywords (Processed from Data

Analyzer) Resume experience (Processed from Data

Analyzer)

INDEXER (CONTD)

During Index time

Document Booster Documents matching perfectly with query for

keywords and experience fields, receives higher score except title.

Ultimately these will help us in ranking the matched document in upper position.

QUERY PROCESSING

Since we have two indexers, we have two types of query

Job postings (search in resume index) Resume (search in job posting index)

Input from the users We take HTML form based input from the users

Query Processing Perform the same steps of Doc Analyzer

RANKING & RETRIEVAL During Index time

Document Booster Documents matching perfectly with query for

keywords and experience fields, receives higher score except title.

Ultimately these will help us in ranking the matched document in upper position.

Document Scoring Function: TF-IDF, BM 25

SYSTEM DESIGN

Backend design: Run as a service on Apache Tomcat server 6.0 Java

Client Connectivity: Java Server Page (JSP)

Front End Design: HTML

DEMO

System Demo

EVALUATIONoEvaluate the performance we choose

● Mean Average Precision (MAP)

oEvaluate Methodologies● Resume selection: We carefully identify 2 resumes

from our dataset.

● Job postings selection: Then we carefully labeled 10 job postings as relevant to those selected 2 resumes

● Mixed up these relevant job postings with some more 20 randomly picked job postings from data set.

● Then calculate the MAP of our System using the top 5 results and find out the MAP 0.3395 but traditional systems have only 0.295.

JOB PREDICTION

Until now we have performed two types of searching:

For a given input Resume, perform search on the job posting index

For a given input Job posting, perform search on the resume index

Can we do something more using exiting

resources?

JOB PREDICTION (CONTD.)

Perform Resume search on the Resume index. Why?

Intuition: People with similar looking resume might be

eligible for similar job!!

Methods: Find similar resumes Find the companies in those resumes Recommend those companies

JOB ANALYTICS

• Goals:● How fast are jobs being filled?● How fast are jobs being posted?● When is the best time to apply?

• Filled Positions:

JOBS IN THE USA

WORLDWIDE JOBS

PROGRAMMING LANGUAGESFacebook: 92.3%IBM: 23.9%Google: 5.8%

FUTURE WORKResume Feedback SuggestionsWhat skills or experience do you need to be qualified for a certain job?

Discover Patterns in Job-Hunting Seasons What time of year are jobs posted most frequently?

Build a Personal DatabaseReceive notifications of job posts that match your interests and skill level

REFERENCES [1] Y. Lu, S. El Helou, and D. Gillet. A recommender

system for job seeking and recruiting website. In Proceedings of the 22nd international conference on World Wide Web companion , pages 963{966.International World Wide Web Conferences Steering Committee, 2013.

[2] R. Rafter, K. Bradley, and B. Smyth. Automated collaborative ltering applications for online recruitment services. In Adaptive Hypermedia and Adaptive Web-Based Systems , pages 363{368. Springer, 2000.

TEAM CONTRIBUTIONS

Mustafiz: NLP and IR system, JSP Backend, Google Crawler

Sam: Crawler structure and database Ellie: IBM Crawler, Front end UI John: Job analytics