Content Analysis Techniques to Ease Browsing with Handhelds - PowerPoint PPT Presentation

1 / 46
About This Presentation
Title:

Content Analysis Techniques to Ease Browsing with Handhelds

Description:

Content Analysis Techniques to Ease Browsing with Handhelds. Jalal Mahmud. Yevgen Borodin ... Browsing with Handhelds: Content Analysis Techniques: - Model ... – PowerPoint PPT presentation

Number of Views:57
Avg rating:3.0/5.0
Slides: 47
Provided by: anus7
Category:

less

Transcript and Presenter's Notes

Title: Content Analysis Techniques to Ease Browsing with Handhelds


1
Content Analysis Techniques to Ease Browsing with
Handhelds
Jalal Mahmud Yevgen Borodin I.V. Ramakrishnan
Department of Computer Science State University
of New York at Stony Brook Stony Brook, NY 11794
2
Outline
  • Browsing with Handhelds
  • Content Analysis Techniques
  • - Model-directed Web Transaction
  • - Merchant-Side Web Transaction
  • - Context Browsing with Mobile
  • - Context-directed Web Transaction
  • Evaluation
  • Future Work



3
Browsing with Handheld
User needs to do a lot of scrolling to get to the
relevant content
Relevant Content
4
Problems
  • Small Screens Offer Narrow Interaction Bandwidth.
  • Unable to convey the Richness of the Web content.
  • Involves a Lot of Horizontal and Vertical
    Scrolling.
  • Tedious to Get to the Pertinent Content in a
    Page.
  • This is worse when one is interested in Web
    transactions (e.g. buying books, paying utility
    bills).



5
Our Approach
  • Filter Away Irrelevant Content and Only Present
  • Relevant Content
  • First Present the Relevant Content.

6
Model-directed Web Transaction
  • Web Transaction Examples
  • - Buying a CD Player from
    Bestbuy
  • - Paying Utility Bills
    Online
  • Web Transaction Characteristics
  • - A Sequence of Steps
  • - Each Step is Based on User-Selected
    Operation
  • Two aspects of a Web transaction
  • - Semantic Concept
  • - Process Model

7
Semantic Concepts
8
Process Model
SEARCH FORM CONCEPT
submit_searchform
1
item_select
TAXONOMY CONCEPT
9
Process Model
item_select
select_item_category
1
submit_searchform
10
Process Model
SEARCH FORM CONCEPT
submit_searchform
item_select
SEARCH RESULT CONCEPT
11
Process Model
item_select
item_select
1
submit_searchform
add_to_cart
select_item_category
2
submit_searchform
12
Process Model
1 - START STATE
add_to_cart
6 - FINAL STATE
show_item_detail
add_to_cart
check_out
3
4
item_select
item_select
view_shoppingcart
item_select
select_item_category
submit_searchform
Submit_searchform
1
6
check_out
add_to_cart
submit_searchform
check_out
select_item_category
2
5
submit_searchform
view_shoppingcart,
update_shoppingcart
continue_shopping
Model-driven transaction
13
Process Model
1 - START STATE
add_to_cart
6 - FINAL STATE
show_item_detail
add_to_cart
check_out
3
4
item_select
item_select
view_shoppingcart
item_select
select_item_category
submit_searchform
Submit_searchform
1
6
check_out
submit_searchform
add_to_cart
check_out
select_item_category
2
5
submit_searchform
view_shoppingcart,
update_shoppingcart
continue_shopping
Model-driven transaction
14
Evaluation Results
Process Model
  • Built using Automata Learning Techniques
  • Training Data
  • Over 200 Transaction Sequences Collected from
    over 30 Sites
  • Recall / Precision
  • 90 / 96 for Books domain
  • 86 / 88 for Consumer Electronics domain
  • 84 / 92 for Office Supplies domain

15
Concept Extraction
16
Evaluation Results
Concept Extraction
  • Developed a Statistical Model for Each Concept
    using Machine Learning Techniques
  • Training Data
  • Used Labeled Concepts from Over 100 Pages
    Collected from Two Dozen Sites

17
Evaluation Results
18
Model-directed Web Transaction on Handheld
Guide-O-Mobile
19
Outline
  • Browsing with Handhelds
  • Content Analysis Techniques
  • - Model-directed Web transaction
  • - Merchant-Side Process Modeling
  • - Context-Browsing with Mobile
  • - Context-Directed Web Transaction
  • Evaluation
  • Future Work



20
Client-Side Process Modeling Problems
  • Client-Side Process Modeling in Guide-O-Mobile.
  • Process Model is Stored in Client Side.
  • Separate Process Model Needed for Each Domain.
  • Performance Largely Depends on Concept
    Extraction.

21
Merchant-Side Process Modeling
  • Labeled Web Content with Semantic Annotations.
  • Content Providers will Label their Web Content.
  • XHTML will be Used to
  • Label Relevant Content in the Web Sites
  • Describe Process Models Specific to the Sites.
  • Mobile Users will Use the System to
  • Easily Identify Relevant Information.
  • Perform On-Line Transactions.

22
Prototype Implementation
  • XHTML tags
  • , , ,
    , , ,
    , , , detail, , and .

23
Outline
  • Browsing with Handhelds
  • Content Analysis Techniques
  • - Model-directed Web Transaction
  • - Merchant-side Web Transaction
  • - Context-Browsing with Mobile
  • - Context-Directed Web Transaction
  • Evaluation
  • Future Work



24
Context Browsing with Mobile
  • On Following a Link
  • Collect Context of the Link
  • Identify the Relevant Section on the Next Page
  • Using the Context
  • Present the Relevant Section.
  • Context Browsing
  • Reduces Information Overload
  • Makes Mobile Browsing Faster.

25
Context-directed Browsing
26
Context-directed Browsing
27
How Do We Find Relevant Content?
  • Finding What is Important on a Web Page
  • Is Subjective on Any Distinct Page
  • Can be Inferred in a Sequence of Pages

28
(No Transcript)
29
(No Transcript)
30
(No Transcript)
31
Context Browsing with Mobile CMo Prototype
32
Product Search Using CMo
33
Outline
  • Browsing with Handhelds
  • Content Analysis Techniques
  • - Model-directed Web transaction
  • - Merchant-side Web transaction
  • - Context-Browsing with Mobile
  • - Context-directed Web Transaction
  • Evaluation
  • Future Work



34
Context-directed Web Transaction
  • No Process Model
  • Contextual Browsing with a Domain-Dependent
    Knowledge-Base
  • Relevant Segment Identification Using Contextual
  • Browsing
  • Concept Segment Identification Using
    Knowledge-Base and Heuristics Algorithms

35
Context-directed Web Transaction Prototype
System
  • The Online Shopping Knowledge-Base Consists of
    the Following Few Concepts
  • SearchForm, AddToCart, Taxonomy,
    ShoppingCart, Checkout, etc.
  • Implementing the Prototype is a Work in Progress.

36
Evaluation Guide-O-Mobile Experimental Set-Up
  • Guide-O-Mobile
  • 1.2 GHz desktop with 256 MB RAM
  • Client-Server Model
  • Client 400 MHz iPaq with 64 MB RAM
  • Server Core Guide-O System
  • Evaluation
  • Over two dozen CS graduate students
  • Over 30 web sites spanning Books, Consumer
    Electronics and Office Supplies domains

37
Evaluation Guide-O Mobile
Guide-O-Mobile Overall Time Performance
38
Evaluation Guide-O Mobile
Guide-O-Mobile Overall Time Performance with
standard deviation
39
Evaluation Guide-O Mobile
Guide-O-Mobile Interaction Time
40
Evaluation Guide-O Mobile
Guide-O-Mobile Interaction Time Performance with
standard deviation
Standard Deviation
41
EvaluationCMo Experimental Set-Up
  • Client-Server Model
  • Client IPAQ Pocket PC equipped with Microsoft
    Pocket PC operating system with wireless Internet
    connectivity.
  • Server Core CMo System
  • Evaluation
  • 8 CS graduate students completing 8 tasks (8
    times each) on 8 Web sites from News and Shopping
    Domain.

42
EvaluationCMoPerformance of Context
Identification
43
Evaluation CMoRelevant Information
Identification
44
Browsing Efficiency with CMo
45
Conclusion and Future Work
  • Port all the Server Steps to the Handheld.
  • Extend the Mozilla's Minimo Mobile Browser with
    CMo Functionalities.
  • Mining Transactional Models from Contextual
    Information.

46
  • Questions?
Write a Comment
User Comments (0)
About PowerShow.com