Andreas Hotho is directing the Bibsonomy project at Kassel University’s Knowledge and Data Engineering resarch group; Bibsonomy is a social bookmark and publication sharing system catering especially for researchers who, next to bookmarkingm also wish to manage publications. Next to other interesting things, Bibsonomy supports the import of bookmarks from del.icio.us, Firefox bookmarks and local BibTex files. Being a project led by a university’s computer science department, Bibsonomy is at the same time the result, the object and a stimulus for research in the area of tagging and folksonomies. Andreas describes this double appeal of folksonomies to both ordinary people and researchers in a 12 seconds vlog post:

Andreas Hotho’s statement about folksonomies and research (see www.bibsonomy.org) on 12seconds.tv

One of the outcomes of the research into folksonomies is FolkRank, a search algorithm that exploits the structure of folksonomies; the name reveals that it was inspired by PageRank, but as the graph of folksonomy structures does not correspond to the web graph, some adaptations had to be made. The specifics of these adaptations can be found in an online article by Andreas and his colleagues: “FolkRank: A Ranking Algorithm for Folksonomies” (PDF, 268 KB).

Andreas Hotho’s talk more specifically addressed the search for methods to identify tags which describe the same concept (or a more specific / a more general concept respectively) within a folksonomy. He suggested two approaches:

1. Applying measures directly to folksonomy statistics, allowing to describe tags as a vector; e.g. co-occurrence frequency and FolkRank could serve as a similarity measure (with these two having a tendency towards high-frequency tags) or a cosine method (which is more likely to produce “siblings”)
2. Looking up tags in an external thesaurus/vocabulary (for instance achieving semantic grounding by mapping a tag and its most similar tags with Wordnet Synsets)

Future areas of interest within folksonomy research Andreas proposed were trend detection, tag recommendation, detecting spam (a major challenge!), logsonomies (i.e. the structure of search engine query log files) and learning synsets, hierarchies, and structures of folksonomies. Andreas Hotho can be contacted via his homepage, if you have any further questions regarding Bibsonomy, FolkRank or this present piece of research.

Another presentation dedicated to folksonomies – and the presentation that won my personal presentation design award – was “Seeding, Weeding, Fertilizing – Different Tag Gardening Activities for Folksonomy Maintenance and Enrichment” by Katrin Weller and Isabella Peters, both from the Dept. of Information Science at Heinrich Heine University in Düsseldorf. The entire presentation was designed to match the CI of Tagcare, a tag gardening tool that is hopefully going to go online soon.

The term “Tag Gardening” was borrowed from James Governor who wrote in a 2006 blogpost:

“Like plants or animals, tags evolve in an emergent fashion, open to hybridisation. Stewardship can help grow and put roots down.

Helping the darwinian process is tag gardening.

Tag gardening is about taking tags in the wild and tending to them, or identifying a wild tag that will do well in your south facing IT

garden. I am talking about domestication here.

Just like there are professional bloggers i am pretty sure some parties will emerge that get paid for their abilities.”

I seriously hope that the latter is going to come true, even though I have the feeling that most providers will continue to consider user input and effort pro bono work!

Katrin Weller’s intro (Isabella Peters had excused herself) focused on the well-known problems with tags and folksonomies, e.g. :

• spelling variants, synonyms, abbreviations, different natural languages
• adhoc or personal functions of tags other than content description (e.g. “toread”, “@Henry”, “nicepic”)
• flatness of tag clouds which allows for browsing by popularity, but not by semantic interrelations

She further distinguished three levels where tag or tag cloud improvement becomes relevant:

• single document vs document collection level
• Single user vs collaborative level
• intra- and cross plattform level (e.g. different tagging conventions, tag separation with comma or blank space, etc)

To push the gardening metaphor even further, Kathrin presented us their ideas of weeding, seeding, fertilizing etc.:

Weeding
The weeds in this case are “bad” tags like spam or misspelled tags (weed: any plant that crowds out cultivated plants)
Aim: enhancing recall and a consistent indexing vocabulary
Achieved by: type-ahead functionality, editing funcionalities, natural language processing, user guidelines for indexing and retrieval, nomination of authorized users as gardeners

Seeding
Seeding in folksonomies means to expand frequently used tags by more specific tags (called “baby tags” or “seedlings” by Katrin Weller; seedling: young plant or tree grown from a seed)

Landscaping
The idea of landscaping here means to create “flower beds” through identifying species of tags, e.g. by similarity.
Aim: enhancing precision and expressiveness

Fertilizing
Fertilizing in this context means to combine folksonomies with other knowledge organization systems (KOS): thesauri, controlled vocabularies, ontologies, etc. (fertilizer: any substance such as manure or a mixture of nitrates used to make soil more fertile). Fertilizing might work both ways, Katrin suggested: a folksonomy might be fertilized with the semantic structure of a KOS, or a KOS enhanced by terms from a folksonomy.

And finally TagCare: The ambitious plan is to have a system that allows to import tag clouds from Flickr, deli.icio.us and Bibsonomy, cleanse out dissimilarities between tags, add hierarchical structure to the tag clouds, allow the user to view tag statistics and probably also to have community features, such calibrating one’s tags with those of the chief gardener or to activate collaborative spam elimination. It is going to be a free service, and if you want to be notified when it goes live, you might want to send an email to Katrin.

This full-service proposal for tag gardening does of course sound brilliant – yet is it going to be feasible, on a technical level? In the post-presentation discussion, somebody mentioned Faviki, which relies on DBpedia concepts to solidify the tag cloud. It didn’t exactly seem as though the TagCare team had already thought along these (semantic web) lines, even though this perfectly corresponded to their ‘Fertilizing’ idea. But if TagCare solely relies on good human gardeners, how long will it take until they have gained a big enough community to stimulate someone’s altruism? The idea of tag gardening of course is beautiful, and I am curious to learn more about the technology it is going to use.

Other folksonomy and tag related presentations that I was unable to attend or am unable to describe now, after the 10th hour of my 2nd day at TRIPLE-I, with a band performing folkore music involving yodeling and probably Schuhplattler right outside of this room:

• Quality Metrics for Tags of Broad Folksonomies (Celine Van Damme, Martin Hepp, Tanguy, Coenen, University of Brussels, Universität der Bundeswehr München
• Providing Multi Source Tag Recommendations in a Social Resource Sharing Platform (Martin Memmel, Michael Kockler, Rafael Schirru, German Research Centre for Artificial Intelligence DFKI)
• Semantic Tagging and Inference in Online Communities, Yildirim Ahmet, Ãœsküdarli Suzan, BoÄŸaziçi University
• Using Visual Features to Improve Tag Suggestions in Image Sharing Sites (Mathias Lux, Oge Marques, Arthur Pitman, Klagenfurt University)
• Harnessing Wikipedia for Smart Tags Clustering (Maria Grineva, Maxim Grinev, Denis Turdakov, Pavel Velikhov, Russian Academy of Sciences)

Please leave a comment if you think that any of the above needs correction.

EDIT: I got the chance to record another 12 seconds definition (and am thinking of setting up a video glossary for the Semantic Web now): Rolf Sint from Salzburg Research explains what folksonomies are and why folksonomies and ontologies go together well in 12 seconds! Rolf is also involved in the KiWi project, which aims to develop a wiki-based knowledge management system boosted by semantic technologies.

Rolf Sint explains folksonomies and their relation to ontologies on 12seconds.tv

Source: Wikipedia

This is great news! In February, I wrote for the first time about the Zemanta browser plug-in prototype which was supposed to allow you to enhance your blog’s content by automatically suggesting links (e.g. to Wikipedia or news pages) and pictures (e.g. on Flickr), based on semantic analysis of your text. Today Andraz from Zemanta notified me that they went live – and the working version is even cooler than the demo they had on their website in February: In February, you had to enter text and hit a button to ‘zemify’ the text – but the current Zemanta comes as a WordPress plug-in. Every 300 characters as you type the plug-in suggests further links and tags which you can apply all at once or by clicking on each one you want – and that is of course MUCH MUCH more convenient than going to a website, copying the URL, highlighting the word and hitting the link button in WP.

The next cool feature is that a side bar shows related content (articles and pictures) on the web – which you can simply add to your blog post by, again, simply clicking on them. Extremely cool! And yes: This very blog entry has been enhanced with Zemanta!

But of course there are a number of glitches in this early version… (and how wouldn’t there be any, as they need feedback to improve):

• The amount of code that is added to your blog entry is a bit intimidating. Adding links runs smoothly, as those links are added to text you’ve already written – but it would be cool to be given the opportunity to decide whether one wants their ‘rich’ links (with title, relation and class attributes) or just plain ones.
• A little footer, explaining that the text was enhanced with Zemanta, is automatically added. Might sound fair enough – but it would be nicer if that were a voluntary option and didn’t happen automatically. Of course you can still remove that footer – but having to opt out is not the same as voluntarily opting in.
• Adding a picture also automatically adds more code (span tags with e.g. margin attributes) than seems necessary – I’d rather have a plain image link (where I can easily define the size of the image myself by specifying width and alignment) than those six (!) lines of code that are pasted into my editor at the moment. It just takes far too long to scan this huge amount of information to see how it can be altered.
• The quality of link and tag suggestions can still be improved (of course); ‘URL’ or ‘the web’ and actually not even ‘Flickr’ (because everyone knows Flickr, right?) are not a tremendous enhancement in the link department. Maybe they’ll be able to track which suggestions are used and which aren’t, and are thus able to identify the empty ones (in the same way that Google disregards ‘a’ or ‘the’ in searches). What’s going to be more difficult is to automatically identify which PHRASES should be linked – as most people (I think? I do) tend to link phrases, and not just single words. Most links in this post, and all pictures, were automatically added by Zemanta.
• Final suggestion: The image gallery is nearly to small to assess whether the suggested images are suitable or not – but I wouldn’t know how to make them much smaller really. What’s great though is that it automatically shows which pictures you have already used and which you haven’t – so that you can automatically remove the used ones by hitting ‘minus’ in the gallery preview. At the moment, the gallery suggestions only vaguely correspond to my content – it’d probably easier if I wrote about kitten and horseys though.

That much about my feedback. I’ll keep testing Zemanta for while, and am keen to see how it is going to improve over the next weeks!