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Low information quality is one of the reasons why information extraction initiatives fail. Incomplete information has a pervasive negative impact on downstream processing steps. This work addresses this problem with a novel information extraction approach, which integrates data mining and information extraction methods into a single complementary approach in order to benefit from their respective...
This paper presents an entity answer extraction method based on list web table. Firstly, extract table from page using the features of web page table and label, segment the table that includes the potential entity answers by calculating the relevance of web table's title and query context, merge the table elements of each column according to table properties, and merge the web table's title with the...
Entity extraction involves multi-factors, and the different factor has an impact on the answer in varying degrees, this paper presents a machine learning approach to parameter learning for entity answer. Firstly, in view of characteristics of the Question Answering System (QA), we define three elements of the text score, passage score and entity score which influenced the answer extraction, also give...
Word Sense Disambiguation (WSD) is the task of selecting the meaning of a word based on the context in which the word occurs. The principal statistical WSD approaches are supervised and unsupervised learning. The Lesk method is an example of unsupervised disambiguation. We present a measure for sense assignment useful for the simple Lesk algorithm. We use word co-occurrences of the gloss and the context,...
Techniques for automatic annotation of spoken content making use of speech recognition technology have long been characterized as holding unrealized promise to provide access to archives inundated with undisclosed multimedia material. This paper provides an overview of techniques and trends in semantic speech retrieval, which is taken to encompass all approaches offering meaning-based access to spoken...
In our daily life we frequently use mobile devices to interact with the people and things on the Internet. However, finding the right things when needed is getting difficult and frustrating. In this paper, we introduce a relatively new problem of non-collaborative personal interest mining using contexts and ratings available for items of interest. We present multi-step algorithms to extract personal...
The paper describes the development and usage of a grammar developed to extract definitions from documents. One of the most important practical usages of the developed grammar is the automatic extraction of definitions from web documents. Three evaluation scenarios were run, the results of these experiments being the main focus of the paper. One scenario uses an e-learning context and previously annotated...
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