Multimodal Attribute Extraction
نویسندگان
چکیده
Given the large collections of unstructured and semi-structured data available on the web, there is a crucial need to enable quick and efficient access to the knowledge content within them. Traditionally, the field of information extraction has focused on extracting such knowledge from unstructured text documents, such as job postings, scientific papers, news articles, and emails. However, the content on the web increasingly contains more varied types of data, including semi-structured web pages, tables that do not adhere to any schema, photographs, videos, and audio. Given a query by a user, the appropriate information may appear in any of these different modes, and thus there’s a crucial need for methods to construct knowledge bases from different types of data, and more importantly, combine the evidence in order to extract the correct answer.
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عنوان ژورنال:
- CoRR
دوره abs/1711.11118 شماره
صفحات -
تاریخ انتشار 2017