G7.0 - Collaborative Searcher™

In the spring of 2007 the Collaborative Searcher™ (CS) was launched. The CS is a fast fuzzy search engine that uses social intelligence to optimize the search results. Focus for the CS - like all Avail's modules - was performance, simplicity and social intelligence. Our aims were:

1. to create a search engine with outstanding performance
   
2. make the implementation and administration as easy as possible with no or minimum impact on existing architecture
   
3. use the social intelligence to optimize the search results

Today the CS runs live on Ellos (part of Redcats Nordic), DVD.co.uk and Home Entertainment (part of Bonniers).

In essence the CS does three things; searches, finds related words and collaborative searches.

1 Searches
The CS has a normal text logical search. This handles fuzzy searches and has very good performance. The reindexing of a large dataset (more than 2 million products) takes less than 5 minutes. The CS uses the same filtering system as the rest of the modules. This means that the searches can be sorted on any data you choose to upload and support multiple sort orders which enables sorting on the English, German, Swedish, French and so on alphabets. The search results can be filtered on any combinations of categories. The rule system allows creation of rules filters. For example, return only search results that cost less than 10 Euros and have been released the last year.

2 Finds clusters of related words
Using social intelligence the CS can learn which words belong to each other according to the view of the customers. For example, the word "Apple" has three meanings to users on a book site.

• For most people Apple means a computer or the company. The related words in this cluster were mac, macintosh, g5, jobs and so on.
• The second most likely meaning was the fruit. The related words in the cluster were gardening, tree, pruning and so on.
• At a distant third meaning was the meaning the record label with only one word in the cluster; Beatles.

Making the related words clickable and the click leading to a new search including the clicked on word, yields a search navigation system which the customer can use to find the product he or she is looking for. This is to the best of our knowledge a brand new way of navigating a site. We know that Google has a similar functionality but it does not work in the same way and we beat them to it.

3 Collaborative Searches
The collaborative searches are social intelligence searches. Instead of searching just on the search phrase submitted by the user, the search engine automatically adds the related words from the first cluster to the search. For example, if a user searches on just "harry" on a book site today we know that the user is looking for Harry Potter books in general and specifically the first and seventh book. It is difficult or impossible for a purely text-logical search engine to understand that this is what the users are looking for and return these books among the first results. The Collaborative Searcher™ would append the related words from the first cluster transforming the search on "harry" to a search on "harry potter rowling hallows deathly stone sorcerer prince blood" thus returning the most relevant results first.

A common headache for people that have been administrating a search engine is the list of synonyms. The related words mechanism is a replacement for synonyms. The related words are how customers perceive that words are related to each other in the closed world of the site.