Name
Abstract | ||
|---|---|---|
This paper presents the first evaluation framework for Web search query segmentation based directly on IR performance. In the past, segmentation strategies were mainly validated against manual annotations. Our work shows that the goodness of a segmentation algorithm as judged through evaluation against a handful of human annotated segmentations hardly reflects its effectiveness in an IR-based setup. In fact, state-of the-art algorithms are shown to perform as good as, and sometimes even better than human annotations a fact masked by previous validations. The proposed framework also provides us an objective understanding of the gap between the present best and the best possible segmentation algorithm. We draw these conclusions based on an extensive evaluation of six segmentation strategies, including three most recent algorithms, vis-a-vis segmentations from three human annotators. The evaluation framework also gives insights about which segments should be necessarily detected by an algorithm for achieving the best retrieval results. The meticulously constructed dataset used in our experiments has been made public for use by the research community. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2348283.2348401 | international acm sigir conference on research and development in information retrieval |
Keywords | DocType | Volume |
web search query segmentation,segmentation algorithm,possible segmentation algorithm,vis-a-vis segmentation,human annotation,extensive evaluation,best retrieval result,ir-based evaluation framework,human annotated segmentation,evaluation framework,segmentation strategy,information retrieval | Conference | abs/1111.1497 |
Citations | PageRank | References |
13 | 0.62 | 21 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rishiraj Saha Roy | 1 | 112 | 15.17 |
| Niloy Ganguly | 2 | 1306 | 121.03 |
| Monojit Choudhury | 3 | 346 | 48.32 |
| Srivatsan Laxman | 4 | 421 | 21.65 |