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Enhancing the Navigability of Social Tagging Systems with Tag Taxonomies
 

Enhancing the Navigability of Social Tagging Systems with Tag Taxonomies

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    Enhancing the Navigability of Social Tagging Systems with Tag Taxonomies Enhancing the Navigability of Social Tagging Systems with Tag Taxonomies Presentation Transcript

    • Enhancing the Navigability of Social Tagging Systems with Tag Taxonomies Christoph Trattner & Christian K¨rner & Denis Helic o KMI, TU Graz September 8, 2011Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 1 / 26
    • Introduction “Tagging gained tremendously in popularity over the past few years”Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 2 / 26
    • Introduction Figure: Tags on FlickrChristoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 3 / 26
    • Introduction Figure: Tags on AmazonChristoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 4 / 26
    • Introduction Figure: Tags on LastFMChristoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 5 / 26
    • Introduction What we also like about tags, apart form the fact that they represent a cheap and light-weight alternative to common key-word based semantic enrichment, is the fact that they allow us to invent tools to explore or navigate an information system in a light-weight and concept driven manner. A popular example of such a tool are tag taxonomies!Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 6 / 26
    • Introduction Q: What is a tag taxonomy? A: A tool that allows us to navigate information items in an information system in a concept driven and hierarchical manner. Figure: Tag TaxonomyChristoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 7 / 26
    • Introduction Popular examples of tag taxonomy induction algorithms are: The graph based approach of Heymann (Heymann et al. 2009) Affinity Propagation (Lerman et al. 2010) Hierarchical K-Means (Dhillon et al. 2001)Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 8 / 26
    • Why usefulness of tag taxonomies for navigation is limited? What we also observed in recent research regarding tagging is the fact that tag based navigation has also it’s limitations (Helic et al. 2010). The problem with tagging is basically the fact that people do not apply tags to all resources of an information system system in a uniform manner.Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 9 / 26
    • Why usefulness of tag taxonomies for navigation is limited? Actually, it was observed (H. Halpin et al. 2007) that the tag distribution of almost all tagging systems follows a power-law function, i.e. there are many tags that refer to a large number of resources. (a) Austria-Forum (b) BibSonomy (c) CiteULike Figure: Tag distributions.Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 10 / 26
    • Why usefulness of tag taxonomies for navigation is limited? Hence, to navigate from one resource to another resource in an information system with the help of a tag taxonomy the user would have to click many many times in the worst case to reach a desired target resource. Figure: Result list of the tag “blog” in the bookmarking system Delicious.Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 11 / 26
    • Why usefulness of tag taxonomies for navigation is limited? Now, to support the user in the process to also navigate to the resources of a tagging system in an efficient manner, we invented the approach of the so-called tag-resource taxonomies. Car Car Tire Motor Tire Motor Mercedes VOLVO VW BMW VW BMW VW BMW (a) Tag Taxonomy (b) Tag-Resource Taxonomy Figure: Tag Taxonomy vs. Tag-Resource Taxonomy. The beauty of such tag-resource hierarchies is that the result lists are limited to a certain branching factor b and the maximum number of clicks is bounded by log(n), where n are the number of resources.Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 12 / 26
    • Why usefulness of tag taxonomies for navigation is limited? Sample calculations of a tag taxonomy vs. a tag-resource taxonomy for the max number of clicks for three different tagging datasets with branching factor b = 10. Austria-Forum BibSonomy CiteULike max{click(Ttag )} 184 5,278 20,799 max{click(Tres )} 6.1 7.7 8.5 Table: Tag Taxonomy vs. Tag-Resource Taxonomy.Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 13 / 26
    • Why usefulness of tag taxonomies for navigation is limited? Sample calculations of a tag taxonomy vs. a tag-resource taxonomy for the mean number of clicks for three different tagging datasets with branching factors ranging from b = 2 − 10. b Austria-Forum BibSonomy CiteULike mean{click(Tres )} 2 14.2 17.8 19.8 mean{click(Ttag )} 2 29.5 22.4 30.7 mean{click(Tres )} 5 6.1 7.6 8.5 mean{click(Ttag )} 5 11.6 9.2 12.3 mean{click(Tres )} 10 4.3 5.3 5.9 mean{click(Ttag )} 10 6.4 5.6 7.3 Table: Tag Taxonomy vs. Tag-Resource Taxonomy.Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 14 / 26
    • Creating tag-resource Taxonomies “How do we create tag-resource hierarchies?”Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 15 / 26
    • Creating tag-resource Taxonomies Actually, the first step to create a tag-resource hierarchy is to create a resource hierarchy out of a tagging dataset. 1. Computer Degree centrality for each resource of the tagging dataset and take the most general resource as our root 2. Compute cosine-similarity for all resources that are related to the root node 3. Re-rank nodes according to their cosine*centrality values 4. Attach max. b resources as childs to the root. 5. Set next child as root and go to step 2.Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 16 / 26
    • Creating tag-resource Taxonomies To generate the actual tag-resource taxonomy we invented a hierarchical labeling algorithm. Basically the algorithm works as follows: 1. Traverse the resource taxonomy in left-order and calculate a co-occurance vector for the currently processed resource. 2. Remove all tags from the co-occ. vector that are not in the tag set of the currently processed resource. 3. Try to apply most general tag of the co-ooc. vector. If the candidate tag has already been applied to one of the parent resources of the currently processed resource, take the next candidate tag from the co-occ. vector.Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 17 / 26
    • Evaluating Tag-Resource Taxonomies In order to evaluate our approach, we conducted basically 3 different experiments As dataset for our analysis we used a tagging dataset from a large Wiki based information system called the Austria-Forum.Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 18 / 26
    • Evaluating Tag-Resource Taxonomies Since our tag-taxonomy induction algorithm is not to 100% free of collisions, we conducted a simple experiment were we measured the number of collisions that occur during the labeling process. Example of a collision: car > bmw > bmw For that purpose we generated three different tag-resource taxonomies with different branching factors ranging from b = 2 − 10 and investigated the collision rate. Name b n CR (%) Res2 2 19,430 0.1% Res5 5 19,430 0.2% Res10 10 19,430 0.2% Table: Collision Rates (CR) for different resource taxonomies with different branching factor b.Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 19 / 26
    • Evaluating Tag-Resource Taxonomies In the second experiment we measured the semantic structure of the tag-resource taxonomy compared to popular tag taxonomy induction algorithms such as Heymann, K-Means, Affinity Propagation and Co-Occurance As measure for this experiment we used Taxonomic Recall/Prec. and Overlap. As Ground truth we used the Germanet ontholoy For the experiment we again generated three different tag-resource taxonomies with different branching factors b.Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 20 / 26
    • Evaluating Tag-Resource Taxonomies 0.4 Taxonomic F−Measure 0.35 Taxonomic Overlap 0.3 Count (1 = 100%) 0.25 0.2 0.15 0.1 0.05 0 Res2 Res5 Res10 Deg/Cooc Aff. Prop K−Means Heymann Figure: Results of the semantic evaluation of the three generated tag-resource taxonomies Res2, Res5 and Res10.Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 21 / 26
    • Evaluating Tag-Resource Taxonomies In the third and last experiment a user study was conducted to evaluate weather our approach is also useful for humans and could be used in a practical setting To compare our approach against a golden standard we used for the experiment so far best known tag taxonomy induction algorithm (Deg/Cooc) To measure the performance of our approach, we invited 9 test users to judge 200 tag trails extracted from both hierarchiesChristoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 22 / 26
    • Evaluating Tag-Resource Taxonomies To ensure that the user would not know which trail she is actually judging, we mixed the trails up uniform at random To actually evaluate the trails, we asked our test users to start from the most left concept and to move on to the most right concept in the trail The evaluation schema given to the user was the following: Classification Description Correct Correct hierarchy relation Related Correct relation, but not hierarchical or reverse hierarchical Equivalent Synonym Not Related The relations do not have anything to do with each other Unknown The evaluator does not recognize the meaning of the tag(s) Table: Classification Labels for the User Evaluation.Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 23 / 26
    • Evaluating Tag-Resource Taxonomies The user study showed a high performance of our approach compared to a Deg/Cooc tag taxonomy. Name b Correct (%) Related (%) Equivalent (%) Not Related (%) Unknown(%) Deg/Cooc10 10 33.2 27.3 13 21.9 5.1 Res10 10 27.3 36.2 12.3 19.8 4.2 Table: Results of the empirical analysis of the tag-resource taxonomy with branching factor b = 10 compared to a Deg/Cooc tag taxonomy with branching factor b = 10.Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 24 / 26
    • Summary We showed that tag taxonomies are in general not very well suited for finding resources in an efficient number of clicks. To tackle that issue we introduced a novel approach of the so-called tag-resource hierarchies. We illustrated in theory that with the approach of a tag-resource taxonomy it is possible to navigate to resources efficiently. Additionally to these findings, we introduced an algorithm to generate such hierarchies and presented in a number of experiments that proofed that tag-resource taxonomies perform on a semantic level nearly as good or even better than popular tag taxonomy approaches.Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 25 / 26
    • End of presentation Thank you very much for your attention! Christoph Trattner (ctrattner@iicm.edu)Christoph Trattner & Christian K¨rner & Denis Helic (KMI, Navigability of Social Tagging Systems with Tag Taxonomies o Enhancing the TU Graz) September 8, 2011 26 / 26