1.
Transforming Current Awareness Through RSS Lisa Rogers Research Associate Institute for Computer Based Learning Heriot-Watt University, Edinburgh, Scotland ticTOCs and Gold Dust Projects ticTOCS & Gold Dust

2.
Can RSS really transform current awareness? <ul><li>RSS Current Situation </li></ul><ul><li>ticTOCs Project </li></ul><ul><li>Gold Dust Project </li></ul><ul><li>The way forward? </li></ul>

3.
Current Situation? <ul><li>RSS for Sharing Information. </li></ul><ul><li>What are the uses in research? </li></ul><ul><li>RSS adoption. </li></ul><ul><li>What should information professionals do? </li></ul><ul><li>Information Overload: Is RSS contributing or easing the situation? </li></ul>

4.
ticTOCs Project <ul><li>Journal Tables of Contents Service </li></ul><ul><li>Aggregates TOC feeds. </li></ul><ul><li>Find, Save, Display and Export latest Tables of Contents from over 12,000 journals ~430 publishers </li></ul><ul><li>Accommodates both users of RSS and non users </li></ul><ul><li>http://www.tictocs.ac.uk </li></ul>

5.
ticTOCs Demonstration

6.
Guidelines for Publishers of TOCs <ul><li>Use RSS 1.0 specification </li></ul><ul><li>Use RSS 1.0 Modules (dc, prism, content) ‏ </li></ul><ul><li>Don’t include HTML in the standard RSS elements </li></ul><ul><li>Use the RSS Content Module to present HTML marked up content. </li></ul><ul><li>Ensure feeds are valid </li></ul><ul><li>Include abstracts </li></ul><ul><li>Understand the purpose of each feed </li></ul><ul><li>Do not restrict access to TOC RSS feeds. </li></ul><ul><li>Provide up-to-date OPML file(s) </li></ul>

7.
ticTOCs Data Set <ul><li>tiCTOCS text file http://www.tictocs.ac.uk/text.php </li></ul><ul><li>Tab Delimmited File with ticTOCs ID, Journal Title, Feed URL, ISSN, eISSN </li></ul>1 Nature http://www.nature.com/nature/current_issue/rss 0028-0836 1476-4679 2 Nature Biotechnology http://www.nature.com/nbt/current_issue/rss 1087-0156 1546-1696 3 19th-Century Music http://caliber.ucpress.net/action/showFeed?ui=0&mi=0&ai=s2&jc=ncm&type=etoc&feed=rss 0148-2076 1533-8606

8.
Using tiCTOCs data set

9.
Gold Dust

10.
Tracking <ul><li>ticTOCs usage: Articles viewed, exported or clicked on in ticTOCs are collected. </li></ul><ul><li>User Submitted Documents: Journal articles written by or of interest to user. </li></ul>

11.
Profiling <ul><li>Collated Articles are fed into NaCTeMs TerMine Web Service </li></ul><ul><li>Personal Interest Profiles (PIPs) are produced </li></ul><ul><li>Also trialled ExtMiner: Open Source tool combining structured search and document clustering techniques. </li></ul><ul><li>compressive strength, 3 </li></ul><ul><li>crack initiation, 6 </li></ul><ul><li>shear stress, 4 </li></ul><ul><li>critical shear stress, 9.50978 </li></ul><ul><li>threshold value, 4 </li></ul><ul><li>microcrack initiation, 2 </li></ul><ul><li>martensitic steel, 2 </li></ul><ul><li>impact response, 3 </li></ul><ul><li>composite laminate, 3 </li></ul><ul><li>structural variation, 2 </li></ul><ul><li>health monitoring, 2 </li></ul><ul><li>composite structure, 2 </li></ul><ul><li>failure mode, 2 </li></ul><ul><li>damage detection, 3 </li></ul><ul><li>unified approach, 2 </li></ul>

12.
Matching <ul><li>The Users profile is matched to items from the various categories of RSS Feeds </li></ul>Calls for Papers New Items in Institutional Repositories and Subject Repositories Funding Opportunity News Patents Press Releases Professional Society News Engineering News Feeds Component Announcements Teaching and Learning Resources Forthcoming Conferences and Events Theses and Dissertations News from JISC Services and Projects Suppliers New Book Announcements Standards Others Journal Articles

13.
Delivery

14.
Results <ul><li>Item considered ‘Gold Dust’ if rated 8-10 </li></ul><ul><li>Tested 4 Methods in two Iterations </li></ul><ul><li>2 nd Iteration was better 15% and 14% </li></ul><ul><li>Best Categories were: </li></ul><ul><ul><li>Journal Articles </li></ul></ul><ul><ul><li>Items from IR and SRs, </li></ul></ul><ul><ul><li>Theses and Dissertations </li></ul></ul><ul><ul><li>Engineering News Feeds </li></ul></ul><ul><li>Best Results for a User was 63% ‘Gold Dust’ </li></ul>

15.
Observations <ul><li>Need more and better initial usage data </li></ul><ul><li>Require method of stopping generic terms </li></ul><ul><li>Matching against items of a similar style to input data gives better results </li></ul><ul><li>If a user’s research area is more specific results are likely to be better </li></ul>

16.
Conclusions <ul><li>What should Information Professionals do? </li></ul><ul><li>What about RSS feed providers? </li></ul><ul><li>What about using RSS and text mining as a recommender system? </li></ul>

17.
Questions? <ul><li>Questions? </li></ul><ul><li>Email L.J.Rogers@hw.ac.uk </li></ul><ul><li>Twitter @lisajrogers </li></ul>