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- item-1 hasContent munmun-de-choudhury.
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- item-2 hasContent winter-mason.
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- 1011 creator alexander-kotov.
- 1011 creator chengxiang-zhai.
- 1011 type InProceedings.
- 1011 label "Towards Natural Question Guided Search".
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- 1011 abstract "Web search is generally motivated by an information need. Since asking well-formulated questions is the fastest and most natural way to obtain information for human beings, almost all queries posed to search engines correspond to some underlying questions, which reflect the user's information need. Accurate determination of these questions may substantially improve the quality of search results and usability of search interfaces. In this paper, we propose a new framework for question-guided search, in which a retrieval system would automatically generate potentially interesting questions to users based on the search results of a query. Since the answers to such questions are known to exist in the search results, these questions can potentially guide users directly to the answers that they are looking for, eliminating the need to scan the documents in the result list. Moreover, in case of imprecise or ambiguous queries, automatically generated questions can naturally engage users into a feedback cycle to refine their information need and guide them towards their search goals. Implementation of the proposed strategy requires new methods for content indexing, question generation, ranking and feedback, all of which are examined in detail. The proposed strategy has been implemented in a prototype of a question-guided search engine, which has been evaluated by real users on a subset of Wikipedia. Evaluation results show the promise of this new question-guided search strategy.".
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- 1011 keyword "Natural language".
- 1011 keyword "spell correction".
- 1011 keyword "suggestions".
- 1011 keyword "summarization".
- 1011 title "Towards Natural Question Guided Search".
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- item-1 hasContent alexander-kotov.
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- item-2 hasContent chengxiang-zhai.
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- 1016 creator brennan-moore.
- 1016 creator david-karger.
- 1016 creator max-van-kleek.
- 1016 creator mc-schraefel.
- 1016 creator paul-andre.
- 1016 type InProceedings.
- 1016 label "Atomate It! End-user context-sensitive automation using heterogeneous information sources on the Web".
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- 1016 abstract "The transition of personal information management (PIM) tools off the desktop to the Web presents an opportunity to augment these tools with capabilities provided by the wealth of real-time information readily available. In this paper, we describe a next-generation personal information assistance engine that lets end-users delegate to it various simple context- and activity-reactive tasks and reminders. Our system, Atomate, treats RSS/ATOM feeds from social networking and life-tracking sites as sensor streams, integrating information from such feeds into a simple unified RDF world model representing people, places and things and their time-varying states and activities. Combined with other information sources on the web, including the user's online calendar, web-based e-mail client, news feeds and messaging services, Atomate can be made to automatically carry out a variety of simple tasks for the user, ranging from context-aware filtering and messaging, to sharing and social coordination actions. Atomate's open architecture and world model easily accommodate new information sources and actions via the addition of feeds and web services. To make routine use of the system easy for non-programmers, Atomate provides a constrained-input natural language interface (CNLI) for behavior specification, and a direct-manipulation interface for inspecting and updating its world model.".
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- 1016 keyword "Context-Aware interactions".
- 1016 title "Atomate It! End-user context-sensitive automation using heterogeneous information sources on the Web".
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- item-1 hasContent max-van-kleek.
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- 1051 creator hugo-zaragoza.
- 1051 creator jeffrey-pound.
- 1051 creator peter-mika.
- 1051 type InProceedings.
- 1051 label "Ad-Hoc Object Retrieval in the Web of Data".
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- 1051 abstract "Semantic Search vaguely refers to a loose set of concepts, challenges and techniques having to do with harnessing the information of the growing Web of Data (WOD) for Web search. Here we propose a formal model of one specific semantic search task: ad-hoc object retrieval. We show that this task provides a solid framework to study some of the semantic search problems currently tackled by commercial Web search engines. We connect this task to the traditional ad-hoc document retrieval and discuss appropriate evaluation metrics. Finally, we carry out a realistic evaluation of this task in the context of a Web search application.".
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- 1051 keyword "Semantic search".
- 1051 keyword "entity retrieval".
- 1051 keyword "geo/temporal search".
- 1051 keyword "sub/super-documents".
- 1051 title "Ad-Hoc Object Retrieval in the Web of Data".
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