In this paper we study the effectiveness of applying sentence compression on an extraction based multi-document summarization system. Our results show that pure syntactic-based compression does not improve system performance. Topic signature-based reranking of compressed sentences does not help much either. However reranking using an…
We describe iNeATS – an interactive multi-document summarization system that integrates a state-of-the-art summarization engine with an advanced user interface. Three main goals of the system are: (1) provide a user with control over the summarization process, (2) support exploration of the document set with…
A new algorithm is proposed for removing large objects from digital images. The challenge is to fill in the hole that is left behind in a visually plausible way. In the past, this problem has been addressed by two classes of algorithms: (i) "texture synthesis"…
In this paper we present an empirical study of the potential and limitation of sentence extraction in text summarization. Our results show that the single document generic summarization task as defined in DUC 2001 needs to be carefully refocused as reflected in the low inter-human…
Following the recent adoption by the machine translation community of automatic evaluation using the BLEU/NIST scoring process, we conduct an in-depth study of a similar idea for evaluating summaries. The results show that automatic evaluation using unigram cooccurrences between summary pairs correlates surprising well with…
Dense stereo is a well studied problem in computer vision. Generally dense stereo algorithms provide only a single estimate of disparity, ignoring uncertainty in the disparity map. Here however, we present a new, linear-time, exact method for recovering entire distributions for disparity at all pixels.…
This paper addresses the problem of extracting three-dimensional geometric information from a single, uncalibrated image of a scene.
We describe an in-depth study of using a dictionary (WordNet) and web search engines (Altavista, MSN, and Google) to boost the performance of an automated question answering system, Webclopedia, in answering definition questions. The results indicate applying dictionary and web-based answer reranking together increase the…
We present a parametric method to automatically identify people in monocular low-resolution video by estimating the height and stride parameters of their gait. Stride parameters (stride length and cadence) are functions of body height, weight, and gender Previous work has demonstrated an effective use of…
This paper describes the Webclopedia Question Answering system, in which methods to automatically learn patterns and parameterizations are combined with hand-crafted rules and concept ontologies. The source for answers is a collection of 1 million newspaper texts, distributed by NIST. In general, two kinds of…
In this paper we discuss manual and automatic evaluations of summaries using data from the Document Understanding Conference 2001 (DUC-2001). We first show the instability of the manual evaluation. Specifically, the low interhuman agreement indicates that more reference summaries are needed. To investigate the feasibility…
NeATS is a multi-document summarization system that attempts to extract relevant or interesting portions from a set of documents about some topic and present them in coherent order. NeATS is among the best performers in the large scale summarization evaluation DUC 2001.
