Appen Uses Humans to Improve Non-English Search Relevance
March 21, 2014
The Appen explanation titled Query Relevance delves into the work that the language, search and social technology company has done recently to improve natural language search. Linguist PhD Julie Vonwiller founded the company in 1996 with her engineer husband Chris Vonwiller. In 2010, Appen merged with Butler Hill Group and began making strides in language resources, search, and text. The article explores the issues at hand when it comes to natural language search,
“Even a query as seemingly simple as the word “blue” could be looking for any of the following: a description or picture of the color, a television show, a credit card, a misspelling of an electronic cigarette brand, or a rap artist. By analyzing what the most likely user intent is and returning valid and appropriate results in the correct order of relevance, we encourage a relationship whereby the user will return again and again to our client’s search engine.”
Appen has established a “global network” of locals who are trained experts in the language and local culture. This team allows for the most accurate interpretations of queries from regional users. The company is continually working to improve their processes, both through collaboration with users and advances in the program to provide the best possible results.
Chelsea Kerwin, March 21, 2014