Contextual Query Intent Extraction for Paid Search Selection
نویسندگان
چکیده
Paid Search algorithms play an important role in online advertising where a set of related ads is returned based on a searched query. The Paid Search algorithms mostly consist of two main steps. First, a given searched query is converted to different sub-queries or similar phrases which preserve the core intent of the query. Second, the generated sub-queries are matched to the ads bidded keywords in the data set, and a set of ads with highest utility measuring relevance to the original query are returned. The focus of this paper is optimizing the first step by proposing a contextual query intent extraction algorithm to generate sub-queries online which preserve the intent of the original query the best. Experimental results over a very large real-world data set demonstrate the superb performance of proposed approach in optimizing both relevance and monetization metrics compared with one of the existing successful algorithms in our system.
منابع مشابه
Characterizing User Search Intent and Behavior for Click Analysis in Sponsored Search
Interpreting user actions to better understand their needs provides an important tool for improving information access services. In the context of organic Web search, considerable effort has been made to model user behavior and infer query intent, with the goal of improving the overall user experience. Much less work has been done in the area of sponsored search, i.e., with respect to the adver...
متن کاملContextual query classification in web search
There has been an increasing interest in exploiting multiple sources of evidence for improving the quality of a search engine’s results. User context elements like interests, preferences and intents are the main sources exploited in information retrieval approaches to better fit the user information needs. Using the user intent to improve the query specific retrieval search relies on classifyin...
متن کاملDiscovering Popular Clicks\' Pattern of Teen Users for Query Recommendation
Search engines are still the most important gates for information search in internet. In this regard, providing the best response in the shortest time possible to the user's request is still desired. Normally, search engines are designed for adults and few policies have been employed considering teen users. Teen users are more biased in clicking the results list than are adult users. This leads...
متن کاملContextual Query Expansion for Acquiring Web Documents
Query expansion is an information retrieval technique in which new query terms are added to the original query terms to improve search performance. Contextual query expansion is major issue in today‟s era. In this paper, contextualization is achieved by performing document extraction and terms extraction activities to the particular domain information source. User query is expanded using docume...
متن کاملRelevant term suggestion in interactive web search based on contextual information in query session logs
This paper proposes an effective term suggestion approach to interactive Web search. Conventional approaches to making term suggestions involve extracting co-occurring keyterms from highly ranked retrieved documents. Such approaches must deal with term extraction difficulties and interference from irrelevant documents, and, more importantly, have difficulty extracting terms that are conceptuall...
متن کامل