III. Collective maps and helping the search & discovery of information
Harnessed collective intelligence creates collective value, built in the form of subject/concept mind maps. These will be generated as a byproduct of the aggregated filtering, annotation and organization of information by users through the maps they made, from which other users shall benefit from—a setup similar to Kaboodle, where users typically search for a given item on Google, save the information on Kaboodle, check if other users actually have performed a similar research to benefit from it, to eventually zero in on the best choice.
Concept/subject maps could be the evolution of an About.com or Wikipedia site with a web 2.0 and mind mapping twist.
Wish #3: Implement backend processes that can:
- Combine the same if not similar maps to form a collective map that grows in real time as users simultaneously add notes and branches
measure similarity of maps the del.icio.us way – from collaborative filtering and/or building a thesaurus database common to everyone so that similar and related terms may be specified or tagged together.
- Recommendations. Generate recommended links supported by and aggregated from the bookmarks of the larger social group through measures of popularity and relationship strength in the form of (among others) commonalities between the same
- Presentation/Navigation. Collapse only parts of maps most relevant to search terms, collective data allows for specificity in search
- Presentation/Navigation. Mouseovers or clicks to final links/leaves will display page as preview DHTML – web2.0 firefox plugin
- Presentation. Option to display user notes and annotations according to most popular (voted/rated, viewed, recommended) users or in groups
- Tracking relevance of suggested results:
- measure amount of time spent per search result by measuring the time between search result links recent and a preceding result; most relevant results could be the longest time among clicked items in comparison to others clicked as well. This approach, however, may not be relevant to users that click on assessed relevant results in separate tabs first before studying all of them and returning to the search results page again to open more links.
- adding personal comments to annotations and notes of others, similar to Amazon’s ‘was this helpful to you’ section
- Syndication. Support public or social network (1st, 2nd degree, artificial) data standards such as FOAF (see also Q & A support) to filter common concept maps