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Despite its substantial coverage, Nom-Bank does not account for all within-sentence arguments and ignores extra-sentential arguments altogether. These arguments , which we call implicit, are important to semantic processing, and their recovery could potentially benefit many NLP applications. We present a study of implicit arguments for a select group of(More)
Nominal predicates often carry implicit arguments. Recent work on semantic role labeling has focused on identifying arguments within the local context of a predicate; implicit arguments, however, have not been systematically examined. To address this limitation, we have manually annotated a corpus of implicit arguments for ten predicates from NomBank.(More)
Motivated by psycholinguistic findings, we are currently investigating the role of eye gaze in spoken language understanding for multimodal conversational systems. Our assumption is that, during human machine conversation, a user's eye gaze on the graphical display indicates salient entities on which the user's attention is focused. The specific domain(More)
Multimodal conversational interfaces provide a natural means for users to communicate with computer systems through multiple modalities such as speech and gesture. To build effective multimodal interfaces, automated interpretation of user multimodal inputs is important. Inspired by the previous investigation on cognitive status in multimodal human machine(More)
Collaborative filtering identifies information interest of a particular user based on the information provided by other similar users. The memory-based approaches for collaborative filtering (e.g., Pearson correlation coefficient approach) identify the similarity between two users by comparing their ratings on a set of items. In these approaches, different(More)
Image annotations allow users to access a large image database with textual queries. There have been several studies on automatic image annotation utilizing machine learning techniques, which automatically learn statistical models from annotated images and apply them to generate annotations for unseen images. One common problem shared by most previous(More)
Multimodal user interfaces allow users to interact with computers through multiple modalities, such as speech, gesture, and gaze. To be effective, multimodal user interfaces must correctly identify all objects which users refer to in their inputs. To systematically resolve different types of references, we have developed a probabilistic approach that uses a(More)
One key to cross-language information retrieval is how to efficiently resolve the translation ambiguity of queries given their short length. This problem is even more challenging when only bilingual dictionaries are available, which is the focus of this paper. In the previous research of cross-language information retrieval using bilingual dictionaries, the(More)
With the emergence of e-commerce systems, successful information access on e-commerce websites becomes essential. Menu-driven navigation and keyword search currently provided by most commercial sites have considerable limitations, as they tend to overwhelm and frustrate users with lengthy, rigid and not very effective interactions. To provide an efficient(More)