5099835
Answering Questions About Moving Objects in Videos
Current question answering systems succeed in many respects regarding questions about textual documents. However, information exists in other media, which provides both opportunities and challenges for question answering. We describe our efforts in extending question answering capabilities to video data: our implemented prototype, Spot, can answer questions about moving objects in a surveillance setting. This novel application of vision and language technology is situated within a larger framework designed to integrate knowledge from multiple domains under a common representation. We believe that our framework will support the next generation of multimodal natural language information access systems.
6918069
Methods for automatically evaluating answers to complex questions
Evaluation is a major driving force in advancing the state of the art in language technologies. In particular, methods for automatically assessing the quality of machine output is the preferred method for measuring progress, provided that these metrics have been validated against human judgments. Following recent developments in the automatic evaluation of machine translation and document summarization, we present a similar approach, implemented in a measure called POURPRE, an automatic technique for evaluating answers to complex questions based on n-gram co-occurrences between machine output and a human-generated answer key. Until now, the only way to assess the correctness of answers to such questions involves manual determination of whether an information “nugget” appears in a system's response. The lack of automatic methods for scoring system output is an impediment to progress in the field, which we address with this work. Experiments with the TREC 2003, TREC 2004, and TREC 2005 QA tracks indicate that rankings produced by our metric correlate highly with official rankings, and that POURPRE outperforms direct application of existing metrics.
9391992
Web question answering: is more always better?
This paper describes a question answering system that is designed to capitalize on the tremendous amount of data that is now available online. Most question answering systems use a wide variety of linguistic resources. We focus instead on the redundancy available in large corpora as an important resource. We use this redundancy to simplify the query rewrites that we need to use, and to support answer mining from returned snippets. Our system performs quite well given the simplicity of the techniques being utilized. Experimental results show that question answering accuracy can be greatly improved by analyzing more and more matching passages. Simple passage ranking and n-gram extraction techniques work well in our system making it efficient to use with many backend retrieval engines.
22235434
The role of context in question answering systems
Despite recent advances in natural language question an-swering technology, the problem of designing effective user interfaces has been largely unexplored. We conducted a user study to investigate the problem and discovered that overall, users prefer a paragraph-sized chunk of text over just an exact phrase as the answer to their questions. Fur-thermore, users generally prefer answers embedded in con-text, regardless of the perceived reliability of the source documents. When users research a topic, increasing the amount of text returned to users significantly decreases the number of queries that they pose to the system, suggesting that users utilize supporting text to answer related ques-tions. We believe that these results can serve to guide future developments in question answering user interfaces.
12592432
User simulations for evaluating answers to question series
Recently, question series have become one focus of research in question answering. These series are comprised of individual factoid, list, and ''other'' questions organized around a central topic, and represent abstractions of user-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 ''QA-styled'' user and an ''IR-styled'' 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.
16198992
Evaluation of resources for question answering evaluation
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.
40521773
Cycle decompositions of crowns
Abstract For an integer n ⩾3, the crown S n 0 is defined to be the graph with vertex set { x 0 , x 1 ,…, x n −1 , y 0 , y 1 ,…, y n −1 } and edge set {x i y j : 0⩽i,j⩽n−1, i≠j} . In this paper we give some sufficient conditions for the edge decomposition of the crown into isomorphic cycles.
14212803
Merging Databases Under Constraints
The problem of integrating information from conflicting sources comes up in many current applications, such as cooperative information systems, heterogeneous databases, and multiagent systems. We model this by the operation of merging first-order theories. We propose a formal semantics for this operation and show that it has desirable properties, including abiding by majority rule in case of conflict and syntax independence. We apply our semantics to the special case when the theories to be merged represent relational databases under integrity constraints. We then present a way of merging databases that have different or conflicting schemas caused by problems such as synonyms, homonyms or type conflicts mentioned in the schema integration literature.
16138730
Group SAX: Extending the Notion of Contrast Sets to Time Series and Multimedia Data
In this work, we take the traditional notation of contrast sets and extend them to other data types, in particular time series and by extension, images. In the traditional sense, contrast-set mining identifies attributes, values and instances that differ significantly across groups, and helps user understand the differences between groups of data. We reformulate the notion of contrast-sets for time series data, and define it to be the key pattern(s) that are maximally different from the other set of data. We propose a fast and exact algorithm to find the contrast sets, and demonstrate its utility in several diverse domains, ranging from industrial to anthropology. We show that our algorithm achieves 3 orders of magnitude speedup from the brute-force algorithm, while producing exact solutions.
8944311
Recent shortcuts: using recent interactions to support shared activities
We present an empirical study of teams that revealed the amount of extraneous individual work needed to enable collaboration: finding references to other people, finding files to attach to email, managing incoming email attachments, managing the variety of files used in shared activities, and tracking what work is owed to others. Much of this work involves finding recently accessed objects that are needed again in the user's current task focus. These observations led to the design of Recent Shortcuts, a tool to help support coordination by making recently used objects easily accessible. Recent Shortcuts enables quick access to people (including groups of people), received attachments, files, and file folders that the user interacted with recently for re-use in the user's current context. Recent Shortcuts makes it easy to use these objects across applications with no additional user input and minimal changes to the user's applications or work practice. Early user experiences with a working prototype led to an extension that integrates recently accessed objects across multiple devices.
207155257
Visually mining and monitoring massive time series
Moments before the launch of every space vehicle, engineering discipline specialists must make a critical go/no-go decision. The cost of a false positive, allowing a launch in spite of a fault, or a false negative, stopping a potentially successful launch, can be measured in the tens of millions of dollars, not including the cost in morale and other more intangible detriments. The Aerospace Corporation is responsible for providing engineering assessments critical to the go/no-go decision for every Department of Defense space vehicle. These assessments are made by constantly monitoring streaming telemetry data in the hours before launch. We will introduce VizTree, a novel time-series visualization tool to aid the Aerospace analysts who must make these engineering assessments. VizTree was developed at the University of California, Riverside and is unique in that the same tool is used for mining archival data and monitoring incoming live telemetry. The use of a single tool for both aspects of the task allows a natural and intuitive transfer of mined knowledge to the monitoring task. Our visualization approach works by transforming the time series into a symbolic representation, and encoding the data in a modified suffix tree in which the frequency and other properties of patterns are mapped onto colors and other visual properties. We demonstrate the utility of our system by comparing it with state-of-the-art batch algorithms on several real and synthetic datasets.