Hajime Morita

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We present a new morphological analysis model that considers semantic plausibility of word sequences by using a recurrent neural network language model (RNNLM). In unsegmented languages, since language models are learned from automatically segmented texts and inevitably contain errors, it is not apparent that conventional language models contribute to(More)
This study proposes a text summarization model that simultaneously performs sentence extraction and compression. We translate the text summarization task into a problem of extracting a set of dependency subtrees in the document cluster. We also encode obligatory case constraints as must-link dependency constraints in order to guarantee the readability of(More)
Many epidemiological studies have shown that coffee consumption reduces the risk of type 2 diabetes mellitus (T2D), although the reasons as to why remain unclear. In this study we investigated the effect of caffeine on pancreatic beta-cell damage in rats using the diabetogenic agent, streptozotocin (STZ). Wistar rats were given intraperitoneal injections of(More)
This is an overview of the NTCIR-12 MobileClick-2 task (a sequel to 1CLICK in NTCIR-9 and NTCIR-10). In the MobileClick task, systems are expected to output a concise summary of information relevant to a given query and to provide immediate and direct information access for mobile users. We designed two types of MobileClick subtasks, namely, iUnit ranking(More)
We propose a new method for query-oriented extractive multi-document summarization. To enrich the information need representation of a given query, we build a co-occurrence graph to obtain words that augment the original query terms. We then formulate the summarization problem as a Maximum Coverage Problem with Knapsack Constraints based on word pairs(More)
We describe our two query-oriented summarization systems implemented for the NTCIR-9 1CLICK task. We regard a Question Answering problem as a summarization process. Both of the systems are based on the integer linear programming technique, and consist of an abstractive summarization model and a model ensuring to cover diversified aspects for answering(More)
We propose a taxonomy of contradictory event pairs and a method for building a database of such pairs. When a dialog system participates in an open-domain conversation with a human, it is important to avoid the generation of utterances that conflict with the context of the dialog. Here, we refer to a pair of events that are not able to co-occur or that are(More)
We propose a new method which enables the training of a kernelized structured output model. The structured output learning can flexibly represent a problem, and thus is gaining popularity in natural language processing. Meanwhile the polynomial kernel method is effective in many natural language processing tasks, since it takes into account the combination(More)
We describe our query-oriented summarization system implemented for the NTCIR-10 1CLICK-2 task. Our system is purely based on a summarization method regarding the task as a summarization process. The system calculates relevant scores of terms for a given query, then extracts relevant part of sentences from input sources. For the calculation of relevant(More)