Digital categorization Stage 1 Multiple concepts are activated Stage 2 Choose ONE of the activated concepts. Categorize it! Note the chosen concept Stage 0 Object worth remembering (article, image…) Cognitive process behind categorization Analysis-Paralysis!

Tagging is simpler Stage 1 Multiple concepts are activated Tag it! Write down all activated concepts Stage 0 Object worth remembering (article, image…) Cognitive process behind tagging

Tagging: Input versus Output Output Structure Input Effort Low High Low High Tag Clouds Hierarchical categorization Facets Clusters Collaborative Filtering If we could get to Facets / clusters from tags, it would be best of both worlds

Getting at structure through tags: (a) Card Sorting http://www.rashmisinha.com/archives/05_02/tag-sorting.html

Getting at structure: (b) Collaborative Filtering Challenges with Input: Getting lazy users to provide input (some indication of interest) Implicit (infer user intention from behavior). e.g., past purchasing behavior on Amazon Explicit (powerful, difficult to get people to rate stuff) e.g., ratings on Pandora, MediaUnbound) Challenges with interface Hard to convey what system is doing (no direct cause & effect as with search) Need to make system logic transparent (e.g., Amazon) Users who liked X, also liked Y Users who searched for X, also liked Y Users who bought X, also bought Y

Challenges with Input: Getting lazy users to provide input (some indication of interest)

Implicit (infer user intention from behavior). e.g., past purchasing behavior on Amazon

Explicit (powerful, difficult to get people to rate stuff) e.g., ratings on Pandora, MediaUnbound)

Challenges with interface

Hard to convey what system is doing (no direct cause & effect as with search)

Need to make system logic transparent (e.g., Amazon)

Users who liked X, also liked Y

Users who searched for X, also liked Y

Users who bought X, also bought Y

Varieties of Collaborative Filtering with Tags Tags as an indicator of interest Tagged url as input, url as output People who like this url also like these other urls Tagged

Tags as an indicator of interest

Tagged url as input, url as output

People who like this url also like these other urls

Tagged

Using tags as semantic information (with CF algorithms) Tags as input: Tags as output (People who use similar tags also use) Tagged urls as input: Tagged urls as output People who tagged similar urls’ also tagged these urls Tag-url conjunction as input: Tagged url’s as output People who tagged similar url’s with similar tags, also tagged other url’s with same tags

Tags as input: Tags as output

(People who use similar tags also use)

Tagged urls as input: Tagged urls as output

People who tagged similar urls’ also tagged these urls

Tag-url conjunction as input: Tagged url’s as output

People who tagged similar url’s with similar tags, also tagged other url’s with same tags

User Experience in such Search/Browse interfaces More of a controlled experience Every movement (forward, making a turn, backwards) is a conscious choice. (need information at every step) User might make mistakes, and retract (go back) a step or two or start again. Each of these is a conscious choice. Like being in control of a car

More of a controlled experience

Every movement (forward, making a turn, backwards) is a conscious choice. (need information at every step)

User might make mistakes, and retract (go back) a step or two or start again. Each of these is a conscious choice.

User Experience with Recommender Systems -user has less control over specifics of the interaction. System does not provide information about specifics of action more of the black box model (some input from user, output from systems). Like riding a roller-coaster

-user has less control over specifics of the interaction.

System does not provide information about specifics of action

more of the black box model (some input from user, output from systems).

Tags & Clusters This idea is not new!

Clusters on Flickr Positives: No effort to name the clusters (makes clusters easy to understand) No fancy visual ways to show the clusters, simple text and image based Clustering tags, rather than items (computationally easier, easier to understand( No Other or Misc category Negatives Hard to understand the overall space and the individual categories Much harder to do with anything but images

Positives:

No effort to name the clusters (makes clusters easy to understand)

No fancy visual ways to show the clusters, simple text and image based

Clustering tags, rather than items (computationally easier, easier to understand(

No Other or Misc category

Negatives

Hard to understand the overall space and the individual categories

Much harder to do with anything but images

Tags & Facets (the holy grail?) You have several orthogonal classifications. For example, Wine.com Wine can be described by type, region, price, vintage. Instead of putting all this in one large hierarchy, you can have several hierarchies Natural afffinity between tags and facets With tags you don’t need to know where stuff lives, just know a few of its descriptors You can have as many facets as you want There are multiple ways to access a piece of content

You have several orthogonal classifications.

For example, Wine.com

Wine can be described by type, region, price, vintage.

Instead of putting all this in one large hierarchy, you can have several hierarchies

Natural afffinity between tags and facets

With tags you don’t need to know where stuff lives, just know a few of its descriptors

You can have as many facets as you want

There are multiple ways to access a piece of content

From tags to Facets More than one way Compute facets from tags in some intelligent manner RawSugar Uses tags Some sort of a taxonomy at the back end to make sense of tags http://www.rawsugar.com/collections/oferben

More than one way

Compute facets from tags in some intelligent manner

RawSugar

Uses tags

Some sort of a taxonomy at the back end to make sense of tags

Chandler approach People tag mail and other items Can promote tags to facets

People tag mail and other items

Can promote tags to facets