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The explosion of multimodal fake news content on social media has sparked widespread concern. Existing multimodal fake news detection methods have made significant contributions to the development of this field, but fail to adequately exploit the ...

In 2000, the author published a new discovery about the same-sex charge produced by friction of the same substance at the ninth electrostatic academic conference of Chinese physical society. This new discovery is of great significance. It opens an ...

This paper uses the depth learning model of sharing parameter to extract entities and relationships. The problems of pipeline model error propagation and ignoring the internal relationship between subtasks, a parameter sharing model is proposed, which ...

Fine-grained sentiment analysis is a useful tool for producers to understand consumers’ needs as well as complaints about products and related aspects from online platforms. In this article, we define a novel task named “Multi-Entity Aspect-Based ...

Query recommendation, which suggests related queries to search engine users, has attracted a lot of attention in recent years. Most of the existing solutions, which perform analysis of users’ search history (or query logs), are often insufficient for ...

Topic models have been widely applied in discovering topics that underly a collection of documents. Incorporating human knowledge can guide conventional topic models to produce topics which are easily interpreted and semantically coherent. Several ...

General-purpose knowledge bases are increasingly growing in terms of depth (content) and width (coverage). Moreover, algorithms for entity linking and entity retrieval have improved tremendously in the past years. These developments give rise to a new ...

In today's computerized and information-based society, individuals are constantly presented with vast amounts of text data, ranging from news articles, scientific publications, product reviews, to a wide range of textual information from social media. ...

With the increasing amounts of data generated in the cyber world the need for an efficient and robust technique has been felt. Keyword based search provides a solution for the problems mentioned before. Keyword search has been proven an effective ...

Entities (e.g., person, movie or place) play an important role in real-world applications and learning entity types has attracted much attention in recent years. Most conventional automatic techniques use large corpora, such as news articles, to learn ...

In this paper we aim at filtering documents containing timely relevant information about an entity (e.g., a person, a place, an organization) from a document stream. These documents that we call vital documents provide relevant and fresh information ...

In this paper we aim at filtering documents containing timely relevant information about an entity (e.g., a person, a place, an organization) from a document stream. These documents that we call vital documents provide relevant and fresh information ...

Nowadays, there are many events reported by News Media everyday, which contains a massive number of news. People are getting more and more interested in understanding how an event evolves after it happens. News related to the same event or similar ...

Results diversification for keyword search on XML documents has attracted considerable attentions from research community in recent years. Though search results were diversified from different perspectives in the existing methods, the effects were still ...

Categorizing entities by their types is useful in many applications, including knowledge base construction, relation extraction and query intent prediction. Fine-grained entity type ontologies are especially valuable, but typically difficult to design ...

The Internet has enabled the creation of a growing number of large-scale knowledge bases in a variety of domains containing complementary information. Tools for automatically aligning these knowledge bases would make it possible to unify many sources of ...

Contemporary psychology has shown that self-theories can have a profound influence on affect and behavior. Entity-theorists, believing their traits are fixed, adopt maladaptive learning strategies in the face of difficulty. In contrast, incremental-...

Generic, reusable ontology elements, such as a foundational ontology?s categories and part-whole relations, are essential for good and interoperable knowledge representation. Ontology developers face the challenge to figure out which category their ...

Topic models, which factor each document into different topics and represent each topic as a distribution of terms, have been widely and successfully used to better understand collections of text documents. However, documents are also associated with ...

TweetSpector is a tool for demonstrating entity-based of retrieval of tweets. The various features of this tool include: entity profile creation, real-time tweet classification, active improvement of the created profiles through user feedback, and the ...