1. User-Friendly Systems Instead of User-Friendly Front-Ends Present user interfaces are not accepted because the underlying systems are too difficult to use. Natural language queries using statistical probability formulas are a possible solution. Four prototype systems were looked at, PRISE, CITE, Muscat, and the News Retrieval Tool.

2. User-Friendly Systems Instead of User-Friendly Front-Ends There are two major problems with the Boolean system –It requires the user to input AND and OR statement. –The results are returned in an unordered list. Statistical retrieval engines allow both a natural language query and returns a list ranked by relevance.

3. User-Friendly Systems Instead of User-Friendly Front-Ends The basic theory is to compare each record in an information file to the users query and estimating the likelihood of relevance. One of the first systems tried was quorum or coordinate matching which performed poorly One of the most efficient ways of weighting terms is through IDF – Inverted Document Frequency.

4. PRISE The similarity of the document and query are found through summing the weights of all matching terms. The goal of this system were only to show that this system could be efficiently implemented. The query was formed using natural language. Results were returned in an ranked list

5. PRISE The scope of the test consisted of 5 different data sets Over 40 users took part, 2/3 of which had never did or seldom used online retrieval systems 9 of the test subjects used Boolean systems regularly 5 of them used Boolean systems occasionally

6. PRISE 53 of the 68 queries retrieved at least 1 relevant document in the top 10. 25 of these relevant documents were the first document retrieved. 10 of the users that had at one time used a Boolean search engine gave the system a favorable review.

7. CITE Developed specifically to access Medline. Uses “free-text” queries against the titles and abstracts in Medline. Users marked the relevant documents returned, then the controlled words from those documents were applied to a new search. No longer in use.

8. Muscat It is based in the probabilistic model by Spark Jones, however it was weighted differently. Could use various query input, from natural language to UDC for Polar Libraries. It has the ability to use a Boolean search in concert with the probabilistic model.

9. News Retrieval Tool Uses a Macintosh based interface where the user can add weight to their terms. The users are allowed to select relevant documents and then research based on those documents. Users can also select key words from a document to become part of the search set.

10. Conclusion These systems fit the requirement that they provide high quality results at real-time speeds. They allow novice users to quickly become successful searchers. By adding successful search engines that cater to the end user these prototypes became user-friendly systems.