/
The Web
The Web

The Web - PowerPoint Presentation

tawny-fly
tawny-fly . @tawny-fly
Follow
108 views | Public

The Web - Description

Changes Everything Jaime Teevan Microsoft Research jteevan The Web Changes Everything Content Changes January February March April May June July August September The Web Changes Everything ID: 541505 Download Presentation

Tags :

web change content pages change web pages content teevan august july june april march february january revisit september revisitation

Please download the presentation from below link :


Download Presentation - The PPT/PDF document "The Web" is the property of its rightful owner. Permission is granted to download and print the materials on this web site for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.

Share:

Link:

Embed:

Presentation on theme: "The Web"— Presentation transcript

Slide1

The WebChanges Everything

Jaime Teevan, Microsoft Research, @jteevanSlide2
Slide3

The Web Changes Everything

Content Changes

January February March April May June July August SeptemberSlide4

The Web Changes Everything

January February March April May June July August September

Content Changes

People Revisit

January February March April May June July August September

Today’s tools focus on the present

But there’s so much more information available!Slide5

The Web Changes Everything

January February March April May June July August September

Content Changes

Large scale Web crawl over time

Revisited pages

55,000

pages crawled hourly for 18+

months

Judged pages (relevance to a query)

6 million pages crawled every two days for 6 monthsSlide6

Measuring Web Page Change

Summary metricsNumber of changesTime between changes

Amount of change

Top level pages change by more and faster than pages with long URLS.

.

edu

and .

gov

pages do not change by very much or very often

News pages change quickly, but not as drastically as other types of pagesSlide7

Measuring Web Page Change

Summary metricsNumber of changesTime between changes

Amount of change

Change curves

Fixed starting point

Measure similarity over different time intervals

Knot pointSlide8

Measuring Within-Page Change

DOM structure changesTerm use changesDivergence from norm

cookbooks

frightfully

merrymaking

ingredientlatkesStaying power in page

Time

Sep. Oct. Nov. Dec.Slide9

Accounting for Web Dynamics

Avoid problems caused by changeCaching, archiving, crawlingUse change to our advantage

Ranking

Match term’s staying power to query intent

Snippet generation

Tom

Bosley

- Wikipedia, the free encyclopediaThomas Edward "

Tom

"

Bosley

(October 1, 1927 October 19, 2010) was an American actor, best known for portraying Howard Cunningham on the long-running ABC sitcom Happy Days.

Bosley

was born in Chicago, the son of Dora

and Benjamin Bosley.

en.wikipedia.org/wiki/tom_bosley

Tom

Bosley - Wikipedia, the free encyclopedia

Bosley died at 4:00 a.m. of heart failure on October 19, 2010, at a hospital near his home in Palm Springs, California. … His agent, Sheryl Abrams, said

Bosley had been battling lung cancer.

en.wikipedia.org/wiki/tom_bosleySlide10

Revisitation on the Web

January February March April May June July August September

Content Changes

People Revisit

January February March April May June July August September

What’s the last Web page you visited?

Revisitation

patterns

Log analysis

Browser logs for

revisitation

Query logs for re-finding

User survey for intentSlide11

Measuring Revisitation

Summary metricsUnique visitors

Visits/user

Time between visits

Revisitation

curvesRevisit interval histogramNormalized

Time

IntervalSlide12

Four

Revisitation

Patterns

Fast

Hub-and-spoke

Navigation within site

HybridHigh quality fast pagesMedium

Popular homepagesMail and Web applicationsSlowEntry pages, bank pages

Accessed via search engineSlide13

Search and Revisitation

Repeat query (33%)microsoft

research

Repeat click (39%)

research.microsoft.com

Query 

msrLots of repeats (43%)Many navigational

Repeat Click

New Click

Repeat Query

33%

29%

4%

New Query

67%

10%

57%

39%

61%Slide14

7thSlide15

How Revisitation and Change Relate

January February March April May June July August September

Content Changes

People Revisit

January February March April May June July August September

Why did you revisit the last Web page you did?Slide16

Possible Relationships

Interested in changeMonitorEffect change

Transact

Change unimportant

Find

Change can interfereRe-findSlide17

Understanding the Relationship

Compare summary metricsRevisits: Unique visitors, visits/user, interval Change: Number, interval, similarity

2 visits/user

3 visits/user

4 visits/user

5

or 6

visits/user

7+

visits/user

Number of changes

Time between changes

Similarity

2 visits/user

172.91

133.26

0.82

3 visits/user

200.51

119.24

0.82

4 visits/user

234.32

109.59

0.81

5

or 6

visits/user

269.63

94.54

0.82

7+ visits/user

341.43

81.80

0.81Slide18

Comparing Change and Revisit Curves

Three pages

New York Times

Woot.com

Costco

Similar change patterns

Different

revisitation

NYT:

Fast

(news, forums)

Woot:

Medium

Costco:

Slow

(retail)Slide19

Comparing Change and Revisit Curves

Three pages

New York Times

Woot.com

Costco

Similar change patterns

Different

revisitation

NYT:

Fast

(news, forums)

Woot

:

Medium

Costco:

Slow

(retail)

TimeSlide20

Within-Page Relationship

Page elements change at different rates

Pages revisited at different rates

Resonance can serve as a filter for interesting contentSlide21
Slide22
Slide23
Slide24

Exposing

Change

Diff-IE

toolbar

Changes to page since your last visitSlide25

Interesting Features

Always on

In-situ

New to you

Non-intrusiveSlide26

Studying Diff-IE

January February March April May June July August September

Content Changes

People Revisit

January February March April May June July August September

SURVEY

How often do pages change?

o

o

o

o

o

How often do you revisit?

o

o

o

o

o

Install

Diff-IE

SURVEY

How often do pages change?

o

o

o

o

o

How often do you revisit?

o

o

o

o

oSlide27

Seeing Change Changes Web Use

Changes to perceptionDiff-IE users become more likely to notice change

Provide better

estimates of how

often content

changesChanges to behaviorDiff-IE users start to revisit moreRevisited pages more likely to have changed

Changes viewed are bigger changesContent gains value when history is exposed

14%

5

1%

53%Slide28

Change Can Cause Problems

Dynamic menus

Put commonly used items at top

Slows menu item access

Search result change

Results change regularly

Inhibits re-finding

Fewer repeat clicks

Slower time to clickSlide29

Change During a Single Query

Results even change as you interact with themSlide30

Change During a Single Query

Results even change as you interact with themMany reasons for changeIntentional to improve ranking

General instability

Analyze behavior when people return after clickingSlide31

Understanding When Change Hurts

MetricsAbandonmentSatisfaction

C

lick position

Time to click

Mixed impact

Results change Above: 4.5% increaseResults change Below: 1.9% decrease

Abandonment

Above

Below

Static

36.6%

43.1%

Change

41.4%

42.3%Slide32

Use Experience to Bias PresentationSlide33

Change Blind Search ExperienceSlide34

The Web Changes Everything

January February March April May June July August September

Content Changes

People Revisit

January February March April May June July August September

Web content changes provide valuable insight

People revisit and re-find Web content

Explicit support for Web dynamics can impact how people use and understand the Web

Relating

revisitation

and change enables us to

Identify pages for which change is important

Identify interesting components within a pageSlide35

Thank you.

Web Content Change

Adar, Teevan, Dumais

&

Elsas.

The Web changes everything: Understanding the dynamics of Web content. WSDM 2009.

Kulkarni, Teevan, Svore & Dumais. Understanding temporal query dynamics.

WSDM 2011

.

Svore,

Teevan

,

Dumais

&

Kulkarni

. Creating temporally dynamic

Web search snippets. SIGIR 2012.Web Page

Revisitation Teevan, Adar, Jones

& Potts. Information re-retrieval: Repeat queries in Yahoo’s logs. SIGIR 2007.Adar, Teevan

& Dumais. Large scale analysis of Web revisitation patterns.

CHI 2008.Tyler & Teevan. Large scale query log analysis of re-finding

. WSDM 2010.Teevan, Liebling & Ravichandran. Understanding and predicting personal navigation. WSDM 2011

.Relating Change and Revisitation

Adar, Teevan & Dumais. Resonance on the

Web: Web dynamics and revisitation patterns. CHI 2009.

Teevan, Dumais, Liebling & Hughes. Changing how people view changes on the Web

. UIST 2009.Teevan, Dumais & Liebling. A longitudinal study of how highlighting

Web content change affects people’s web interactions. CHI 2010.Lee

, Teevan & de la Chica. Characterizing multi-click behavior and the risks and opportunities of changing results during use.

SIGIR 2014.

Jaime Teevan @

jteevan