Graph-based semi-supervised learning (SSL) algorithms have been successfully used to extract class-instance pairs from large unstructured and structured text collections. However, a careful comparison of different graph-based SSL algorithms on that task has been lacking. We compare three graph-based SSL algorithms for class-instance acquisition on a variety of graphs constructed from different ...

This paper presents our system for the “Making Sense of Microposts 2014 (#Microposts2014)” challenge. Our system is based on AIDA, an existing system that links entity mentions in natural language text to their corresponding canonical entities in a knowledge base (KB). AIDA collectively exploits the prominence of entities, contextual similarities, and coherence to effectively disambiguate entit...

Knowledge-based decision support systems (KBDSS) hold up business and organizational decisionmaking activities on the basis of the knowledge available concerning the domain under question. One of the main problems with knowledge bases is that their construction is a time-consuming task. A number of methodologies have been proposed in the context of the Semantic Web to assist in the development ...

DBpedia has been proved to be a successful structured knowledge base, and large scale Semantic Web data has been built by using DBpedia as the central interlinking-hubs of the Web of Data in English. But in Chinese, due to the heavily imbalance in size (no more than one tenth) between English and Chinese in Wikipedia, there are few Chinese linked data are published and linked to DBpedia, which ...

Entity linking and semantic parsing have been shown to be crucial to important applications such as question answering and document understanding. These tasks often require structured learning models, which make predictions on multiple interdependent variables. In this talk, I argue that carefully designed structured learning algorithms play a central role in entity linking and semantic parsing...

Most of knowledge is written in natural language and structured knowledge base includes the partially limited information of them. In QA system perspective, the quality of knowledge base is depends on how it covers the knowledge to answer user’s questions. To deal with this knowledge base construction problem, we define the natural language question sets and answer documents which contains know...

An increasingly relevant theme for knowledge-based systems is how to model and use a large and complex knowledge domain. On the one hand, this involves developing new ideas on a modular construction of a knowledge base and, on the other hand, an appropriate architecture of a knowledge-based system that takes account of such a modular knowledge base. In the HYPERCON project we conceptualize a co...

State-of-the-art recommendation algorithms – especially the collaborative €ltering (CF) based approaches with shallow or deep models – usually work with various unstructured information sources for recommendation, such as textual reviews, visual images, and various implicit or explicit feedbacks. Œough structured knowledge bases were considered in content-based approaches, they have been largel...

Query is an important way of information retrieval. One type of queries is those to search engines, which are lists of keywords without structures. Another type of queries is those to databases or knowledge bases, which must conform to the structure and terminology of the data source (e.g., SQL query to a database). In this paper, we deal with another type of queries: naive user queries–queries...

Large linked data repositories have been built by leveraging semi-structured data in Wikipedia (e.g., DBpedia) and through extracting information from natural language text (e.g., YAGO). However, the Web contains many other vast sources of linked data, such as structured HTML tables and spreadsheets. Often, the semantics in such tables is hidden, preventing one from extracting triples from them...