User evaluations of search engines are expensive and not easy to replicate. The problem is even more pronounced when assessing adaptive search systems, for example system-generated query modification suggestions that can be derived from past user interactions with a search engine. Automatically predicting the performance of different modification suggestion models before getting the users involved is therefore highly desirable. AutoEval is an evaluation methodology that assesses the quality of query modifications generated by a model using the query logs of past user interactions with the system. We present experimental results of applying this methodology to different adaptive algorithms which suggest that the predicted quality of differen...
Users who need several queries before finding what they need can benefit from an automatic search as...
The ongoing explosion of web information calls for more intelligent and personalied methods towards ...
We evaluate the use of clickthrough information as implicit relevance feedback in sessions. We emplo...
User evaluations of search engines are expensive and not easy to replicate. The problem is even more...
User evaluations of search engines are expensive and not easy to replicate. The problem is even more...
and other research outputs AutoEval: an evaluation methodology for evaluating query suggestions usin...
Modern search engines have been moving away from simplistic interfaces that aimed at satisfying a us...
Search engines have become much more interactive in recent years which has triggered a lot of work i...
Interactive information retrieval has received much attention in recent years, e.g. [7]. Furthermore...
Search engines have become much more interactive in recent years which has triggered a lot of work i...
Query suggestion or auto-completion mechanisms are widely used by search engines and are increasingl...
International audienceQuery auto-completion (QAC) is one of the most recognizable and widely used se...
Information retrieval has become very popular over the last decade with the advent of the Web. Neve...
The aim of this thesis is to describe and critically investigate eight different evaluations of the ...
Users tend to use their own terms to search items in structured search systems such as restaurant se...
Users who need several queries before finding what they need can benefit from an automatic search as...
The ongoing explosion of web information calls for more intelligent and personalied methods towards ...
We evaluate the use of clickthrough information as implicit relevance feedback in sessions. We emplo...
User evaluations of search engines are expensive and not easy to replicate. The problem is even more...
User evaluations of search engines are expensive and not easy to replicate. The problem is even more...
and other research outputs AutoEval: an evaluation methodology for evaluating query suggestions usin...
Modern search engines have been moving away from simplistic interfaces that aimed at satisfying a us...
Search engines have become much more interactive in recent years which has triggered a lot of work i...
Interactive information retrieval has received much attention in recent years, e.g. [7]. Furthermore...
Search engines have become much more interactive in recent years which has triggered a lot of work i...
Query suggestion or auto-completion mechanisms are widely used by search engines and are increasingl...
International audienceQuery auto-completion (QAC) is one of the most recognizable and widely used se...
Information retrieval has become very popular over the last decade with the advent of the Web. Neve...
The aim of this thesis is to describe and critically investigate eight different evaluations of the ...
Users tend to use their own terms to search items in structured search systems such as restaurant se...
Users who need several queries before finding what they need can benefit from an automatic search as...
The ongoing explosion of web information calls for more intelligent and personalied methods towards ...
We evaluate the use of clickthrough information as implicit relevance feedback in sessions. We emplo...