QueryCAT is a new search engine that searches Frequently Asked Question pages (FAQs) found at various web sites.

We admit it is an intriguing idea: If you search to fix a problem of a kind (let us say: How to install memory in an iMac?) or information on a site or a company (What is Google?), FAQs often have focused and clear answers.

After all, FAQs are made by web sites to answer common question, thus reducing the amount of repeated queries. Even Pandia has one.

By focusing on FAQs only, QueryCAT, reduces much of the noise that fills up regular search results.

QueryCAT does its job pretty well

Does it work? Yes, our testing indicates that it does work in most cases. A search for “ram ibook” did lead to advice on how to install more memory in these Macs.

In spite of the examples given on the QueryCAT home page, we have found that it helps to avoid natural language questions. “How to install ram in an iBook” gives no results, as it seems QueryCAT is unable to sort out the filler “stop” words (how, to, in, an etc.).

Moreover, it does not seem that QueryCAT catches synonyms. A search for “memory ibook” did not lead to any relevant listings. Still, we do not expect that from the best of search engines, and with some intelligent query formulation, this search engine should help you narrow down the relevant hits.

2 million questions and answers

Kevin Carey of QueryCAT says that they have indexed over 2 million questions and answers using the Alexa Web Search Platform as their crawl and their own unique question recognition technology to power the search.

Submissions

If your own site’s FAQ is not included, you may contact the company. You can browse the sites that have been included to find out.