Abstract. This paper introduces our method for causal knowledge re-trieval from the Internet resources, its results and evaluation of using it in utterance creation process. Our system automatically retrieves common-sensical knowledge from the Web resources by using simple web-mining and information extraction techniques. For retrieving causal knowledge the system uses three of specific several Japanese “if ” forms. From the results we can conclude that Japanese web pages indexed by a common search engine spiders are enough to discover common causal relationships and this knowledge can be used for making Human-Computer Interfaces sound more natural and interesting than while using classic methods
We introduce a method of extracting causal information (e.g., Demand for semi conductor manufacturin...
Background. Automatic extraction of causal chains is valuable for discovering previously unknown and...
Automatic searching, knowledge acquisition and question answering are crying needs among the contemp...
Abstract. In our paper we will introduce ideas for auto-evaluation of common-sensical causations tha...
Acquiring and representing the large body of "common sense " knowledge underlying ordinary...
This paper proposes a method that extracts causal knowledge from news paper articles via clue expres...
The personal stories that people write in their Internet weblogs include a substantial amount of inf...
This dataset contains 136,007 facts (triples) of Japanese commonsense knowledge obtained by translat...
This paper studies the problem of multilingual causal reasoning in resource-poor languages. Existing...
The abundance of information on the internet has impacted the lives of people to a great extent. Peo...
Abstract: In many fields, such as industry, commerce, government, and education, knowledge discovery...
We propose a method for affect analysis of textual input in Japanese supported with Web mining. The ...
Good and generous knowledge sources, reliable and efficient induction patterns, and automatic and co...
In this paper we present a textual dialogue system that uses word associations retrieved from the We...
Abstract: In order to provide useful information about writing and learning Japanese, this paper pro...
We introduce a method of extracting causal information (e.g., Demand for semi conductor manufacturin...
Background. Automatic extraction of causal chains is valuable for discovering previously unknown and...
Automatic searching, knowledge acquisition and question answering are crying needs among the contemp...
Abstract. In our paper we will introduce ideas for auto-evaluation of common-sensical causations tha...
Acquiring and representing the large body of "common sense " knowledge underlying ordinary...
This paper proposes a method that extracts causal knowledge from news paper articles via clue expres...
The personal stories that people write in their Internet weblogs include a substantial amount of inf...
This dataset contains 136,007 facts (triples) of Japanese commonsense knowledge obtained by translat...
This paper studies the problem of multilingual causal reasoning in resource-poor languages. Existing...
The abundance of information on the internet has impacted the lives of people to a great extent. Peo...
Abstract: In many fields, such as industry, commerce, government, and education, knowledge discovery...
We propose a method for affect analysis of textual input in Japanese supported with Web mining. The ...
Good and generous knowledge sources, reliable and efficient induction patterns, and automatic and co...
In this paper we present a textual dialogue system that uses word associations retrieved from the We...
Abstract: In order to provide useful information about writing and learning Japanese, this paper pro...
We introduce a method of extracting causal information (e.g., Demand for semi conductor manufacturin...
Background. Automatic extraction of causal chains is valuable for discovering previously unknown and...
Automatic searching, knowledge acquisition and question answering are crying needs among the contemp...