From the website:
LAILAPS combines a keyword driven search engine for an integrative access to life science databases, machine learning for a content driven relevance ranking, recommender systems for suggestion of related data records and query refinements with a user feedback tracking system for an self learning relevance training.
Features:
- ultra fast keyword based search
- non-static relevance ranking
- user specific relevance profiles
- suggestion of related entries
- suggestion of related query terms
- self learning by user tracking
- deployable at standard desktop PC
- 100% JAVA
- installer for in-house deployment
I like the idea of a recommender system that “suggests” related data records and query refinements. It could be wrong.
I am as guilty as anyone of thinking in terms of “correct” recommendations that always lead to relevant data.
That is applying “crisp” set thinking to what is obviously a “rough” set situation. We as readers have to sort out the items in the “rough” set and construct for ourselves, a temporary and fleeting “crisp” set for some particular purpose.
If you are using LAILAPS, I would appreciate a note about your experiences and impressions.