Cai, F.; Rijke, M. de: Learning from homologous queries and semantically related terms for query auto completion (2016)
0.02
0.021622043 = product of:
0.032433063 = sum of:
0.009385608 = weight(_text_:a in 2971) [ClassicSimilarity], result of:
0.009385608 = score(doc=2971,freq=16.0), product of:
0.05209492 = queryWeight, product of:
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.045180224 = queryNorm
0.18016359 = fieldWeight in 2971, product of:
4.0 = tf(freq=16.0), with freq of:
16.0 = termFreq=16.0
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.0390625 = fieldNorm(doc=2971)
0.023047457 = product of:
0.046094913 = sum of:
0.046094913 = weight(_text_:de in 2971) [ClassicSimilarity], result of:
0.046094913 = score(doc=2971,freq=2.0), product of:
0.19416152 = queryWeight, product of:
4.297489 = idf(docFreq=1634, maxDocs=44218)
0.045180224 = queryNorm
0.23740499 = fieldWeight in 2971, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.297489 = idf(docFreq=1634, maxDocs=44218)
0.0390625 = fieldNorm(doc=2971)
0.5 = coord(1/2)
0.6666667 = coord(2/3)
- Abstract
- Query auto completion (QAC) models recommend possible queries to web search users when they start typing a query prefix. Most of today's QAC models rank candidate queries by popularity (i.e., frequency), and in doing so they tend to follow a strict query matching policy when counting the queries. That is, they ignore the contributions from so-called homologous queries, queries with the same terms but ordered differently or queries that expand the original query. Importantly, homologous queries often express a remarkably similar search intent. Moreover, today's QAC approaches often ignore semantically related terms. We argue that users are prone to combine semantically related terms when generating queries. We propose a learning to rank-based QAC approach, where, for the first time, features derived from homologous queries and semantically related terms are introduced. In particular, we consider: (i) the observed and predicted popularity of homologous queries for a query candidate; and (ii) the semantic relatedness of pairs of terms inside a query and pairs of queries inside a session. We quantify the improvement of the proposed new features using two large-scale real-world query logs and show that the mean reciprocal rank and the success rate can be improved by up to 9% over state-of-the-art QAC models.
- Type
- a