Changes

The Topic Space module (http://minrvaproject.org/modules_topicspace.php ) was developed with an IMLS Sparks! Grant to investigate augmented reality technologies for in-library recommendations. The funding allowed for sustained university community collaboration by the University Library, the Graduate School of Library and Information Science, as well as graduate student programmers sourced from the Department of Computer Science. Collaborators designed app functionality and identified relevant open source libraries that could power optical character recognition (OCR) functionality from within the mobile phone. Topic space allows a user to take a picture of an item's call number in the book stacks. The module will show the user other books that are relevant but that are not shelved nearby. It can also show users books that are normally shelved here but that are currently checked out.

Research questions included development of back end (server-side) pattern matching algorithms for recommendations, and Topic space allows a rapid formative evaluation (user testing to take a picture of an item's call number in Undergrad Library) of interface design that would provide optimal user experience for receiving recommendations and navigation of the book stacks as a context to recommendations. Implications of research and development include best practice recommendations for interface development based on The module will show the formative user studies (eother books that are relevant but that are not shelved nearby.gIt can also show users books that are normally shelved here but that are currently checked out. communicating what works in this area, and what does not), further – Recommendations are based on the back end API developed for Topic Space, grant staff created web based recommendations that could serve as a new way Library of providing readers advisory Congress subject headings and “more like this” recommendations from discovery interfaces library wideILS circulation data which indicate recommendation candidates based on total check-outs.

The recommender references both shelf locations Research questions included development of an item back end (server-side) pattern matching algorithms for recommendations, and a rapid formative evaluation of interface design that would provide optimal user experience for navigation of the book stacks as well as other items circulation counts a context to provide recommendations. Along with the Topic Space native app, grant collaborators prototyped web based recommendations which could serve as a new way of providing readers advisory and “more like this” recommendations from discovery interfaces accessed through desktop browsers. Outcomes of the grant include the availability of the Topic Spaces module on the Android Play store (select Undergrad library for Topic Space module: [https://play.google.com/store/apps/details?id=edu.illinois.ugl.minrva ) Topic Spaces module within Minrva app on the Android Play store] and an experimental ([http://backbonejs.org/ Backbone.js]) Topic Space web app: based [http://minrva-dev.library.illinois.eduTopic Space web app].