@conference {18347,
	title = {Multimodal question answering for mobile devices},
	booktitle = {Proceedings of the 13th international conference on Intelligent user interfaces},
	series = {IUI {\textquoteright}08},
	year = {2008},
	month = {2008///},
	pages = {405 - 408},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {This paper introduces multimodal question answering, a new interface for community-based question answering services. By offering users an extra modality---photos---in addition to the text modality to formulate queries, multimodal question answering overcomes the limitations of text-only input methods when the users ask questions regarding visually distinctive objects. Such interface is especially useful when users become curious about an interesting object in the environment and want to know about it---simply by taking a photo and asking a question in a situated (from a mobile device) and intuitive (without describing the object in words) manner. We propose a system architecture for multimodal question answering, describe an algorithm for searching the database, and report on the findings of two prototype studies.},
	keywords = {Information retrieval, mobile application, pattern matching, Question answering},
	isbn = {978-1-59593-987-6},
	doi = {10.1145/1378773.1378841},
	url = {http://doi.acm.org/10.1145/1378773.1378841},
	author = {Tom Yeh and Darrell,Trevor}
}
@conference {18350,
	title = {Photo-based question answering},
	booktitle = {Proceedings of the 16th ACM international conference on Multimedia},
	series = {MM {\textquoteright}08},
	year = {2008},
	month = {2008///},
	pages = {389 - 398},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Photo-based question answering is a useful way of finding information about physical objects. Current question answering (QA) systems are text-based and can be difficult to use when a question involves an object with distinct visual features. A photo-based QA system allows direct use of a photo to refer to the object. We develop a three-layer system architecture for photo-based QA that brings together recent technical achievements in question answering and image matching. The first, template-based QA layer matches a query photo to online images and extracts structured data from multimedia databases to answer questions about the photo. To simplify image matching, it exploits the question text to filter images based on categories and keywords. The second, information retrieval QA layer searches an internal repository of resolved photo-based questions to retrieve relevant answers. The third, human-computation QA layer leverages community experts to handle the most difficult cases. A series of experiments performed on a pilot dataset of 30,000 images of books, movie DVD covers, grocery items, and landmarks demonstrate the technical feasibility of this architecture. We present three prototypes to show how photo-based QA can be built into an online album, a text-based QA, and a mobile application.},
	keywords = {Computer vision, Information retrieval, Question answering},
	isbn = {978-1-60558-303-7},
	doi = {10.1145/1459359.1459412},
	url = {http://doi.acm.org/10.1145/1459359.1459412},
	author = {Tom Yeh and Lee,John J and Darrell,Trevor}
}
@article {15289,
	title = {User simulations for evaluating answers to question series},
	journal = {Information Processing \& Management},
	volume = {43},
	year = {2007},
	month = {2007/05//},
	pages = {717 - 729},
	abstract = {Recently, question series have become one focus of research in question answering. These series are comprised of individual factoid, list, and {\textquotedblleft}other{\textquotedblright} questions organized around a central topic, and represent abstractions of user{\textendash}system dialogs. Existing evaluation methodologies have yet to catch up with this richer task model, as they fail to take into account contextual dependencies and different user behaviors. This paper presents a novel simulation-based methodology for evaluating answers to question series that addresses some of these shortcomings. Using this methodology, we examine two different behavior models: a {\textquotedblleft}QA-styled{\textquotedblright} user and an {\textquotedblleft}IR-styled{\textquotedblright} user. Results suggest that an off-the-shelf document retrieval system is competitive with state-of-the-art QA systems in this task. Advantages and limitations of evaluations based on user simulations are also discussed.},
	keywords = {Evaluation, Question answering, User simulations},
	isbn = {0306-4573},
	doi = {10.1016/j.ipm.2006.06.006},
	url = {http://www.sciencedirect.com/science/article/pii/S0306457306000963},
	author = {Jimmy Lin}
}
@conference {15305,
	title = {The role of knowledge in conceptual retrieval: a study in the domain of clinical medicine},
	booktitle = {Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval},
	series = {SIGIR {\textquoteright}06},
	year = {2006},
	month = {2006///},
	pages = {99 - 106},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Despite its intuitive appeal, the hypothesis that retrieval at the level of "concepts" should outperform purely term-based approaches remains unverified empirically. In addition, the use of "knowledge" has not consistently resulted in performance gains. After identifying possible reasons for previous negative results, we present a novel framework for "conceptual retrieval" that articulates the types of knowledge that are important for information seeking. We instantiate this general framework in the domain of clinical medicine based on the principles of evidence-based medicine (EBM). Experiments show that an EBM-based scoring algorithm dramatically outperforms a state-of-the-art baseline that employs only term statistics. Ablation studies further yield a better understanding of the performance contributions of different components. Finally, we discuss how other domains can benefit from knowledge-based approaches.},
	keywords = {Question answering, reranking, semantic models},
	isbn = {1-59593-369-7},
	doi = {10.1145/1148170.1148191},
	url = {http://doi.acm.org/10.1145/1148170.1148191},
	author = {Jimmy Lin and Demner-Fushman,Dina}
}
@conference {15304,
	title = {Evaluation of resources for question answering evaluation},
	booktitle = {Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval},
	series = {SIGIR {\textquoteright}05},
	year = {2005},
	month = {2005///},
	pages = {392 - 399},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Controlled and reproducible laboratory experiments, enabled by reusable test collections, represent a well-established methodology in modern information retrieval research. In order to confidently draw conclusions about the performance of different retrieval methods using test collections, their reliability and trustworthiness must first be established. Although such studies have been performed for ad hoc test collections, currently available resources for evaluating question answering systems have not been similarly analyzed. This study evaluates the quality of answer patterns and lists of relevant documents currently employed in automatic question answering evaluation, and concludes that they are not suitable for post-hoc experimentation. These resources, created from runs submitted by TREC QA track participants, do not produce fair and reliable assessments of systems that did not participate in the original evaluations. Potential solutions for addressing this evaluation gap and their shortcomings are discussed.},
	keywords = {pooling, Question answering},
	isbn = {1-59593-034-5},
	doi = {10.1145/1076034.1076102},
	url = {http://doi.acm.org/10.1145/1076034.1076102},
	author = {Jimmy Lin}
}
