facetag: integrating bottom-up and top-down classification in a social tagging system

FaceTagIntegrating Bottom-up and Top-down Classificationin a Social Tagging System

Emanuele Quintarelli, Andrea Resmini, Luca RosatiEuroIA 2006, Berlin

The Evolution of Collaborative Tagging

FaceTag - E. Quintarelli, A. Resmini, L. Rosati - www.facetag.org

An Emerging Approach to Distributed Classification

Collaborative tagging systems are used to organize, browse and share personal collections of resources through the introduction of simple metadata

Folksonomies are user-generated classifications, emerging through bottom-up consensus

The basic idea is simply to make people share items annotated with keywords


Collaborative Tagging Examples

An incomplete list of online tagging systems may include simply, Connotea, magnolia, Taggly, digg, flickr, YouTube, Technorati, 43things.These are in fact web-based collaborative systems for:

building a shared database of items a flat metadata vocabulary metadata driven queries monitoring change in areas of interest discovering emergences or trends


Properties of Folksonomies

Advantages Trade-off between simplicity and precision Match the user’s real needs and language Inclusive (nothing is left out) Help discovery of information and serendipity May be a forced move (the environment makes the difference) Better than nothing (when traditional classification is not viable)

Disadvantages Language issues User Experience issues


As a result of intrinsic language variability, tagging systems are also implicitly plagued by:

Polysemy (window: is that a hole or a glass pane)Homonymy (apple, jaguar)Plurals (blog / blogs, folksonomy / folksonomies)Synonymy (tags, tagging, folksonomy)Ego-oriented tags (toread, funny, interesting etc..)Basic level variations (dog / beagle)

These problems can dramatically reduce the effectiveness of the application and the benefits brought on by tagging systems

Language Issues


User Experience Issues

Tag clouds are visual interfaces for information retrieval that provide a global contextual view of tags assigned to resources in the systemFlat tag clouds are not sufficient to provide a semantic and multidimensional browsing experience. They

have low findability quotient and low scalability have high semantic density where few well-known

topics dominate the scene often follow an alphabetical criterion which limits the

ability to explore the tag cloud cannot visually support semantic relationships often miss to provide complex logical operations


Information seekers in large domains of objects express the desire of having to deal with meaningful groupings of related items, in order to quickly understand relationships and decide how to proceed [Hearst 2006].

How to generate and navigate such groups from a flat set of objects is anyway a totally different matter.

Taxonomies, clustering and faceted classification have been proposed in the past as useful techniques for such purposes

Navigating Large Domains


Taxonomies are coherent and complete systems of meaningful labels which systematically organize a domainTaxonomies are organically crafted before starting to catalogue by professionals who deduce future user needs and content typesThey are authoritative centralized views and allow for greatear precision, avoiding ambiguity: the hierarchy provides context

Taxonomies

Major drawbacks do not have the ability to match the

vocabulary and the ways of thinking of different users

expensive to build and maintain by professional indexers


Clustering is the act of grouping items according to some measure of similarity

It reduces the semantic density and improve the visual consistency of tag clouds

But it generate messy groups, conflates many different dimensions and does not allow refinement and follow-up queries

Users prefer clear hierarchies with categories at uniform levels of granularity over the unpredictable and unlabeled groupings typical of clustering techniques

Clusters


Facets are orthogonal descriptors

(categories) within a metadata system

Each facet has a name and addresses a different conceptual dimension or feature type relevant to the collection

Each object is classified combining labels from different facets

Facets can be Flat or hierarchical Assigned single or multiple

values 23 resources

Facets

Facet name


Hierarchical faceted metadata can be used toadd structure and context to tagsnavigate along several dimensions simultaneouslyseamlessly integrate browsing and searchingrefine and broaden filtering criteria

Facets


Benefits of Facets

Easier to understand the meaning of tags Large tag clouds more browsable Reduction of the mental work (favouring recognition over recall) Better support for exploration, discovery and iterative query

refinement

Usability studies show how this approach is preferred over single hierarchies and clusters


What do we need then?

A middle ground between the pure democracy of bottom-up tagging and the empirical determinism of top-down controlled vocabularies

A new metadata ecology which merges and leverages emerging and traditional tools to improve findability and user experience

This new metadata ecology has to be a fusion, not only a simple process of coexistence


What FaceTag tries to limit the impact of polysemy, homonymy and basic

level variation introducing a multidimensional and semantically richer paradigm

FaceTag aims to improve the usability, findability, browsability, serendipity and scalability of the system

How

FaceTag mixes three contributions to social tagging systems: tag hierarchies facets of tags tagging and searching operate seamlessly

Users provide the faceted hierarchical structure through an intuitive user experience

What FaceTag contributes

Faceted Analysis


How to choose facets

Freehand

each facet is decided on the spotthe subject is freely deconstructed in several aspectseach facet is find out at the momentthe subject is freely deconstructed in several aspects

Standard based

each facet is found out using Ranganathan's or CRG's guidelines

the subject is then deconstructed following a general scheme

the general scheme works as a prototype of every particular faceted scheme


The standard-based approach brings along a number of benefits: it's a standard experience demonstrates it suits several context reduction of risks coming from a subjective perspective

Benefits of standard compliance


Document DateTime[Country]SpacePeople, companiesAgent

Target(e.g. Industry, Health...)

Patient--Byproduct[Deliverables]Product

Activities(e.g. competitive analysis, classification)

Operation --Process[Format]MaterialLanguageProperty--Part

Resources Type(e.g. case study, report...)

Type[Documents, resources]Thing FaceTag facetsCRG standard categories

How we chose facets from the CRG general scheme


document dateDate

dion hinchcliffe morville

People

industry public administration software>companies>google

Usage

discovery>competitive analysis classification>facets navigation design>breadcrumbs

Activities/Subjects

predefined values (based on ISO Standard ISO 639-2)

Language

case study blog>enterprise web

Resources TypesExamplesFaceTag facets

FaceTag facets


Benefits

The blend of facets and tags bring benefits on two axes

Verticalwhen a user associates a keyword to a facet the system suggests similar tags pertaining to the same facet.

Horizontalthe system allows the user to see all the other tags belonging to the same facet.

Horizontal or syntagmatic axisVe

rtic

al o

r pa

radi

gmat

ic a

xis

Open Issues


Title

Topic

Activity

Geo. Area

Other

What's “faceted”

Year

Author

Other

Metadata

Formal properties

Facets

Semantic properties


Faceted Classification is a librarian theory postulating not only a multidimensional approach to an item but also a semantic value of each dimension / facet a specific citation order of such dimensions / facets

In some cases our ‘facets’ are not proper facets, but metadata nevertheless we need such metadata so we may decide for a hybrid approach (facets & metadata)

Labeling of facets / metadata is yet another issue we have to better evaluate

Open issues

Technology Preview: FaceTag


Main page

Facets and pertaining tags

Search box with hinting

Resources with pertaining tags


Using facets for searching: engaging 1 tag

The user chooses 'intranet design' and facets and tags adjust. Breadcrumbing for the engaged tag

appears (top).


Using facets for searching: intersecting 2 tags

The user adds 'article' from another facet.Facets and tags adjust again. Breadcrumbing reflects the

changes. Tags can be disengaged individually


Using facets for searching: final result set

12

3

The user adds 'shiv singh' from yet another facet and finds a final result set. Facets and tags adjust

and show that there is no further possibility to zoom in. Breadcrumbing lists all engaged tags

ready to be disengaged.

facetag: integrating bottom-up and top-down classification in a social tagging system

Education