A Portable & Intelligence Interview System Supervisor: Dr. Cheng Reynold Cheng Man Fung Kevin...
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A Portable & Intelligence Interview System Supervisor: Dr. Cheng Reynold Cheng Man Fung Kevin 3035042423 Fung Chin Pan 3035044641 Lau Hiu Tsun 3035042423
A Portable & Intelligence Interview System Supervisor: Dr.
Cheng Reynold Cheng Man Fung Kevin 3035042423 Fung Chin Pan
3035044641 Lau Hiu Tsun 3035042423 Tso Hei Lok 3035043738
Slide 2
Agenda Background & Related Work Objectives How to Achieve
Development Platform About Our Application Other Technologies
Utilized Demo Conclusion
Slide 3
Background & Related Work
Slide 4
Background Difficulties: Manually Paper Work Process
Time-consuming & costly Onsite Interview Site Problem Bad
Network Connection Problem Decision Making How to select a right
candidate Develop an All-in-one Application
Slide 5
Related Work Existing System Management of the applicants
information Improvement on user interface & presentation of
data Face-to-face Interview No functionality on Video Conferencing
& Recording
Slide 6
Related Work Existing Product Some may include Video
conferencing function Analysis on the effectiveness and consistency
across interviewers Excellent interfaces on managing applicants
information Combined them all together, we get a Portable and
Intelligent Interview System !!
Slide 7
Objective
Slide 8
Diversity Functionalities to manage information Portability
Handling of bad network connection problem Intelligence Analysis on
interviewee
Slide 9
How to Achieve
Slide 10
Diversity All-in-one System Text processing, video
conferencing, recording & etc. A Server allowing access from
around the world Keeping information inside confidential
Slide 11
How to Achieve Portability Online System Offline System To
handle bad network environment Simple to use
Slide 12
How to Achieve Intelligence Statistical Analysis Presentation
of pass data in Charts Comparison among different years of data
Data-mining Text Mining Nave Bayes Classifier
Slide 13
Development Platform
Slide 14
LAMP Ubuntu, Apache Server, MySQL, PHP5 Developed for a long
time Free & Open-source software
Slide 15
Development Platform MVC Model Model View Controller
CodeIgniter Build-in libraries Developed for years
Slide 16
IntelliJ IDEA over Eclipse IDE Smarter auto-completion Class
name / method signatures / variables
Slide 17
IntelliJ IDEA over Eclipse IDE Optimized Default Controls for
Keyboard Refactoring, error fixing, generation of code Key Binding:
Alt-Insert Key Binding: None (Manual Configuration needed)
Slide 18
About Our Application
Slide 19
Business Flow Preparation phase System admin (root) create new
round Add staff (helpers / reviewers) to new round Accept student
applicants
Slide 20
Business Flow Pre-interview phase Helpers provide summary to
student applicants (helpers comment) Reviewers have a chat by
conferencing with the student applicants of interest Staff add new
students manually if necessary
Slide 21
Business Flow On-site interview phase Student Applicants
information prepared Conduct interview and record with video
functionality / camcorder Manage comments and interview videos
(Optional, for offline module only) Upload comments and interview
videos
Slide 22
Business Flow Post on-site interview Sundry Item Review
students full record Automated analysis (on-site comment analysis,
map analysis, chart analysis) Email Functionality
Slide 23
Special Feature Video Conferencing Impossible to arrange
interviews for all the applicants Video Recording Difficult for
some of the reviewers to participate the onsite interview
Slide 24
Special Feature Secure Socket Layer (SSL) application layer
confidentiality symmetric key encryption protection against network
packet capturing software
Slide 25
Special Feature Analysis Map analysis Distribution of the
location of university of current year applicants Comment Analysis
Suggestion of whether the student applicants should be accepted or
not Chart analysis Statistical information of current round for
better planning and coordination in future
Slide 26
No-Network Capability Endure the unstable, low bandwidth or
even no network situation Develop offline module Manage onsite
comments and interview videos Upload the managed comment with one
click when network is stable
Slide 27
Minor items Student list filtering Email Student view
application View application
Slide 28
(fyp14003s1.cs.hku.hk) Online Module @ HKUCS System
Architecture Database HTTPS Offline Module Interne t Sync Student
Applicant Info. / Upload Onsite Comment and Video Geolocation with
Unstable/NO Internet Access Web Server + WebRTC Node JS server
Bring into Bring back Manage student applicants onsite interview
comment and video View student applicants information Interview
round management User account management Comments and video
management Analysis Email functionality
Slide 29
Database Design
Slide 30
Model View Controller (MVC) pattern Passive view model
Controller: communicating component View component: presentation of
data Model: logical evaluation Views further organized Advantage:
separation of code
Slide 31
Decorator Pattern Helps filtering of student applicants list
Reduces number of subclasses by decorator chaining Improves code
quality
Slide 32
Other Technologies Utilized
Slide 33
What is WebRTC? Free open source Real-Time Communications
(RTC)
Slide 34
Why WebRTC? No plug-in open source free Standardized
efficient
Slide 35
WebRTC work on? Chrome Opera Firefox
Slide 36
WebRTC applications do Get streaming Audio Video Other
data
Slide 37
WebRTC applications do Get network information IP address Ports
Coordinate signaling communication Exchange information about media
Communicate streaming
Slide 38
WebRTC implements APIs MediaStream Audio Video
RTCPeerConnection establish communication channel RTCDataChannel
prepare for signaling
Slide 39
MediaStream synchronized streams of media
Slide 40
Signaling not specified by WebRTC standardize Choose by WebRTC
app developer Session Initiation Protocol (SIP) Extensible
Messaging and Presence Protocol (XMPP) XMLHttpRequest (XHR) (We use
Socket.io running on a Node server)
Slide 41
Signaling Exchange three types of information Session control
messages Network configuration Media capabilities
Slide 42
RTCPeerConnection Make the communication of streaming data
between peers. Stable efficient
Slide 43
Something about the system Socket.io running on a Node server
currently support 1 to 1 conferencing
Slide 44
RecordRTC JavaScript-based media-recording library A recording
solution
Slide 45
Security Problems Man in middle Data access right issue Malware
or viruses might be installed
Slide 46
WebRTCs Security secure protocols Datagram Transport Layer
Security (DTLS) The Secure Real-time Transport Protocol (SRTP)
Encryption is mandatory Not a plug-in Media access must be granted
explicitly
Slide 47
Reviewers comment analysis Nave Bayes Classification Efficient
Tutorials from the internet Data preparation Classified comments
into positive and negative Extract words Calculating Conditional
Probabilities Find the largest value to determine the class
Slide 48
Reviewers comment analysis Testing 75% training data, 25%
testing data 24 testing comments (21 positive, 3 negative) Accruacy
90% 19 positive, 5 negative 21 positive comments, 19 of them are
classified as positive 3 negative comments, all of them are
classified as negative
Slide 49
Google map geolocation Send a request to google server Short
form or full name also accepted HKU and The University of Hong Kong
Receive response Put a marker on the map
Slide 50
Google Chart API Show Statistical data Loading some Google
Chart Library Input data Select options Create chart object Showed
on javascript
Slide 51
Technologies Utilized Apache HTTPClient Construction of HTTP
GET and POST messages GSON JSON parsed into and from java object
Guava Creation of structured constant maps by collection
builder.
Slide 52
Demo
Slide 53
Conclusion
Slide 54
Progress- completed Online System E-mail system Video
conferencing Onsite and pre-interview video uploading Search form
of students Managing accounts Managing rounds Analysis on reviewers
comment Reading and modifying comments WebRTC recording in
Firefox
Slide 55
Progress- completed Offline system Synchronization with online
system Video saving Viewing student information Modifying reviewers
comments
Slide 56
Progress- under development Google map analysis Cross-year
analysis UI design Statistical analysis
Slide 57
Progress- to be implemented Beta version for professor testing
Smoke test has done Need further testing for its robustness We are
glad to receive feedbacks for improvement Study WEKA for data
mining Video recording in Google Chrome walk-in student support
Pre-interview conferencing
Slide 58
Future Development WEKA a collection of machine learning
algorithms applied directly to a dataset Java code data
pre-processing, classification, regression, clustering, association
rules, and visualization Cross year analysis Provide more
statistical information
Slide 59
Future Development Walkin student support Student who did not
register Offline system support Pre-interview conferencing No way
to invite a student to start a conferencing Solution A dialog box
to accept the conferencing
Slide 60
Possible Difficulties Reviewers comment analysis Accuracy