Hikaru Yokono

Summarizing a document stream

We introduce the task of summarizing a stream of short documents on microblogs such as Twitter. On microblogs, thousands of short documents on a certain topic such as sports matches or TV dramas are posted by users. Noticeable characteristics of microblog data are that documents are often very highly redundant and aligned on timeline. There can be thousands of documents on one event in the topic. Two very similar documents will refer to two distinct events when the documents are temporally distant. We examine the microblog data to gain more understanding of those characteristics, and propose a summarization model for a stream of short documents on timeline, along with an approximate fast algorithm for generating summary.We empirically show that our model generates a good summary on the datasets of microblog documents on sports matches.

Evaluation Metrics for Machine Reading Comprehension: Prerequisite Skills and Readability

Knowing the quality of reading comprehension (RC) datasets is important for the development of natural-language understanding systems. In this study, two classes of metrics were adopted for evaluating RC datasets: prerequisite skills and readability. We applied these classes to six existing datasets, including MCTest and SQuAD, and highlighted the characteristics of the datasets according to each metric and the correlation between the two classes. Our dataset analysis suggests that the readability of RC datasets does not directly affect the question difficulty and that it is possible to create an RC dataset that is easy to read but difficult to answer.

Document Layout Optimization with Automated Paraphrasing

We introduce a new concept in document layout optimization. In our approach, paraphrase-based~layout~optimization, layout issues (e.g. widows due to poor page breaking) are automatically fixed by rewording the neighboring sentences. Techniques of paraphrasing are borrowed from the field of natural language processing towards this goal, which is the first attempt in the field of document engineering. We implemented a prototype TeX pre/post-processing system that includes two simple paraphrase generators. The experiment shows that our approach is promising and effective for improving document layout.

Incorporating cohesive devices into entity grid model in evaluating local coherence of japanese text

This paper describes improvements made to the entity grid local coherence model for Japanese text. We investigate the effectiveness of taking into account cohesive devices, such as conjunction, demonstrative pronoun, lexical cohesion, and refining syntactic roles for a topic marker in Japanese. To take into account lexical cohesion, we consider a semantic relation between entities using lexical chaining. Through the experiments on discrimination where the system has to select the more coherent sentence ordering, and comparison of the systems ranking of automatically created summaries against human judgment based on quality questions, we show that these factors contribute to improve the performance of the entity grid model.

World History Ontology for Reasoning Truth/Falsehood of Sentences: Event Classification to Fill in the Gaps Between Knowledge Resources and Natural Language Texts

This paper introduces a world history ontology that supports reasoning of truth/falsehood of historical descriptions in natural languages. The core of the ontology includes an event classification according to certain basic properties such as necessary/sufficient conditions for the existence of events in the real world. We will discuss how this ontology functions in solving world history problems in Japan’s National Center Test for University Admissions, especially in the reasoning of “falsehood” of sentences and bridging of the “granularity difference” between target sentences and knowledge resources.