Related papers: Multidimensional Web Page Evaluation Model Using S…
The WorldWideWeb (WWW) is a huge conservatory of web pages. Search Engines are key applications that fetch web pages for the user query. In the current generation web architecture, search engines treat keywords provided by the user as…
The growing proliferation of distributed information systems, allows organizations to offer their business processes to a worldwide audience through Web services. Semantic Web services have emerged as a means to achieve the vision of…
Document-level relation extraction requires integrating information within and across multiple sentences of a document and capturing complex interactions between inter-sentence entities. However, effective aggregation of relevant…
Semantic retrieval (also known as dense retrieval) based on textual data has been extensively studied for both web search and product search application fields, where the relevance of a query and a potential target document is computed by…
Online media provides opportunities for marketers through which they can deliver effective brand messages to a wide range of audiences. Advertising technology platforms enable advertisers to reach their target audience by delivering ad…
Sentiment Analysis is the task of classifying documents based on the sentiments expressed in textual form, this can be achieved by using lexical and semantic methods. The purpose of this study is to investigate the use of semantics to…
The ability to efficiently search pictures with annotated semantics and emotion is an important problem for Human-Computer Interaction with considerable interdisciplinary significance. Accuracy and speed of the multimedia retrieval process…
The abundant semi-structured data on the Web, such as HTML-based tables and lists, provide commercial search engines a rich information source for question answering (QA). Different from plain text passages in Web documents, Web tables and…
As the amount of data on the World Wide Web continues to grow exponentially, access to semantically structured information remains limited. The Semantic Web has emerged as a solution to enhance the machine-readability of data, making it…
Document parsing converts visually rich documents into machine-readable structured representations, forming a crucial foundation for information systems. Although many benchmarks have been proposed for document parsing, they remain…
In recent years, Semantic web has become a topic of active research in several fields of computer science and has applied in a wide range of domains such as bioinformatics, life sciences, and knowledge management. The two fast-developing…
Search services have been developed rapidly in social Internet. It can help web users easily to find their documents. So that, finding a best method search is always an imagine. This paper would like introduce hybrid method of LPageRank…
Document-level relation extraction aims to extract relations among multiple entity pairs from a document. Previously proposed graph-based or transformer-based models utilize the entities independently, regardless of global information among…
Active learning is particularly of interest for semantic segmentation, where annotations are costly. Previous academic studies focused on datasets that are already very diverse and where the model is trained in a supervised manner with a…
The interpretation of the experimental data collected by testing systems across input datasets and model parameters is of strategic importance for system design and implementation. In particular, finding relationships between variables and…
Ranking models are the main components of information retrieval systems. Several approaches to ranking are based on traditional machine learning algorithms using a set of hand-crafted features. Recently, researchers have leveraged deep…
Many computer scientists use the aggregated answers of online workers to represent ground truth. Prior work has shown that aggregation methods such as majority voting are effective for measuring relatively objective features. For subjective…
Semantic segmentation has been widely investigated in the community, in which the state of the art techniques are based on supervised models. Those models have reported unprecedented performance at the cost of requiring a large set of high…
Since the amount of information on the internet is growing rapidly, it is not easy for a user to find relevant information for his/her query. To tackle this issue, much attention has been paid to Automatic Document Summarization. The key…
3D semantic segmentation is a critical task in many real-world applications, such as autonomous driving, robotics, and mixed reality. However, the task is extremely challenging due to ambiguities coming from the unstructured, sparse, and…