Techniques are described herein for training a search query intent classifier using wiki article titles and a search click log. Titles of wiki articles that correspond to links that are associated with a specified wiki article and/or titles of wiki articles that are included in a category that includes the specified wiki article are extracted and included with the title of the specified wiki article in an initial set. Each title in the initial set is correlated with respective clicked URI(s) using a search click log. The initial set is expanded to include search terms that are correlated to the clicked URIs based on the search click log to provide an expanded set. The search query intent classifier is trained to classify search queries with respect to a query intent that is associated with the title of the specified wiki article based on the expanded set.
Please help me write a proper abstract based on the patent claims. CLAIM: 1-20. (canceled) 21. A method comprising: obtaining a designated query intent input to a search query; in response to obtaining the designated query intent, obtaining a first information page corresponding to the designated query intent, wherein the first information page includes a plurality of respective hyperlinks; identifying a secondary information page linked to a hyperlink included in the plurality of respective hyperlinks included in the first information page; extracting a first title of the first information page; extracting a secondary title from the secondary information page; accessing a search click log, and generating an initial key term set including the first title and the secondary title by correlating the first title and the secondary title with at least one respective clicked uniform resource identifier identified by the search click log, wherein the search click log comprises a record of historical search queries and activated documents returned from the historical search queries, and wherein the activated documents have respective uniform resource identifiers; generating an expanded key term set to include the initial key term set expanded to further include search terms correlated to the at least one respective clicked uniform resource identifier; and training a search query intent classifier to classify search queries with respect to the designated query intent based on the expanded key term set. 22. The method of claim 21, further comprising: obtaining the designated query intent from a subsequent search query; and in response to obtaining the subsequent search query corresponding to the designated query intent, controlling the trained search query intent classifier to select online data based on the expanded key term set. 23. The method of claim 22, further comprising: determining a category assigned to the secondary information page; identifying, from a plurality of third information pages associated with the same category assigned to the secondary information page, a plurality of third titles; wherein correlating the first title and the secondary title with at least one respective clicked uniform resource identifier identified by the search click log comprises: correlating each of the first title, the secondary title, and the plurality of third titles with at least one respective clicked uniform resource identifier identified by the search click log. 24. The method of claim 23, wherein generating the expanded key term set comprises: expanding the initial key term set to include search terms, in addition to the first title, the secondary title, and the plurality of third titles, that are correlated to the at least one respective clicked uniform resource identifier based on the search click log to provide the expanded key term set. 25. The method of claim 21, wherein correlating the first title and the secondary title with at least one respective clicked uniform resource identifier identified by the search click log comprises: generating a bipartite graph correlating each of the first title and the secondary title to the at least one respective clicked uniform resource identifier based on the search click log. 26. The method of claim 21, further comprising: assigning a first probability to the first title and to the secondary title; and assigning a second probability to each of the search terms, each second probability being less than the first probability; wherein generating the expanded key term set comprises: expanding the initial key term set to include a first subset of the search terms, the first subset including search terms to which the second probabilities that are greater than a threshold probability are assigned. 27. The method of claim 21, further comprising: generating a negative sample set based on randomly selecting second search terms not included in the expanded key term set; wherein training the search query intent classifier comprises: training the search query intent classifier to classify the search queries with respect to the designated query intent based on the expanded key term set and the negative sample set. 28. The method of claim 21, wherein training the search query intent classifier comprises: training a maxentropy classifier to classify the search queries with respect to the designated query intent based on the expanded key term set. 29. The method of claim 21, wherein training the search query intent classifier comprises: training the search query intent classifier to classify the search queries with respect to the designated query intent based on the expanded key term set and further based on text included in the secondary information page. 30. The method of claim 21, wherein extracting the secondary title comprises: extracting the secondary title from a plurality of secondary information pages corresponding to a plurality of respective hyperlinks included on the first information page. 31. A system comprising: a processor coupled to memory and configured to obtain a designated query intent from a search query; wherein the processor is configured to: in response to obtaining the designated query intent, obtain a first information page corresponding to the designated query intent, wherein the first information page includes a plurality of respective hyperlinks; identify a secondary information page linked to a hyperlink included in the plurality of respective hyperlinks included in the first information page; extract a first title of the first information page; extract a secondary title from the secondary information page; access a search click log, and generate an initial key term set including the first title and the secondary title by correlating the first title and the secondary title with at least one respective clicked uniform resource identifier identified by the search click log, wherein the search click log comprises a record of historical search queries and activated documents returned from the historical search queries, and wherein the activated documents have respective uniform resource identifiers; generate an expanded key term set to include the initial key term set expanded to further include search terms correlated to the at least one respective clicked uniform resource identifier; and train a search query intent classifier to classify search queries with respect to the designated query intent based on the expanded key term set. 32. The system of claim 31, wherein the processor is further configured to: obtain the designated query intent from a subsequent search query; and in response to obtaining the subsequent search query corresponding to the designated query intent, control the trained search query intent classifier to select online data based on the expanded key term set. 33. The system of claim 32, wherein the processor is further configured to: determine a category assigned to the secondary information page; identify, from a plurality of third information pages associated with the same category assigned to the secondary information page, a plurality of third titles; wherein the processor is configured to correlate the first title and the secondary title with at least one respective clicked uniform resource identifier identified by the search click log by: correlating each of the first title, the secondary title, and the plurality of third titles with at least one respective clicked uniform resource identifier identified by the search click log. 34. The system of claim 33, wherein the processor is configured to generate the expanded key term set by: expanding the initial key term set to include search terms, in addition to the first title, the secondary title, and the plurality of third titles, that are correlated to the at least one respective clicked uniform resource identifier based on the search click log to provide the expanded key term set. 35. The system of claim 31, wherein the processor is configured to correlate the first title and the secondary title with at least one respective clicked uniform resource identifier identified by the search click log by: generating a bipartite graph correlating each of the first title and the secondary title to the at least one respective clicked uniform resource identifier based on the search click log. 36. The system of claim 31, wherein the processor is further configured to: assign a first probability to the first title and to the secondary title; and assign a second probability to each of the search terms, each second probability being less than the first probability; wherein the processor is configured to generate the expanded key term set by: expanding the initial key term set to include a first subset of the search terms, the first subset including search terms to which the second probabilities that are greater than a threshold probability are assigned. 37. The system of claim 21, wherein the processor is further configured to: generate a negative sample set based on randomly selecting second search terms not included in the expanded key term set; wherein the processor is configured to train the search query intent classifier by: training the search query intent classifier to classify the search queries with respect to the designated query intent based on the expanded key term set and the negative sample set. 38. The system of claim 31, wherein the processor is configured to train the search query intent classifier by: training a maxentropy classifier to classify the search queries with respect to the designated query intent based on the expanded key term set. 39. The system of claim 31, wherein the processor is configured to train the search query intent classifier by: training the search query intent classifier to classify the search queries with respect to the designated query intent based on the expanded key term set and further based on text included in the secondary information page. 40. A method comprising: determining a category assigned to a first information page, the first information page including a first title associated with a designated query intent and a first body; retrieving a plurality of secondary information pages that are assigned to the same category assigned to the first information page, each secondary information page including a secondary title and a secondary body; extracting a plurality of secondary titles from the plurality of secondary information pages, wherein each of the secondary information pages is different from the first information page; accessing a search click log, and generating an initial key term set including the first title and the plurality of secondary titles by correlating the first title and the plurality of secondary titles with at least one respective clicked uniform resource identifier identified by the search click log, wherein the search click log comprises a record of historical search queries and activated documents returned from the historical search queries, and wherein the activated documents have respective uniform resource identifiers; generating an expanded key term set to include the initial key term set expanded to further include search terms correlated to the at least one respective clicked uniform resource identifier; and training a search query intent classifier to classify search queries with respect to the designated query intent based on the expanded key term set.