Queries in PDFs can be time-consuming and labor-intensive because of the unstructured
nature of the PDF document type and the need for accurate and relevant search results. By …

The search engine process is crucial for document content retrieval. For Khmer documents,
a tool is needed to extract essential keywords. Despite the daily generation of significant …

Search engine has become a fundamental component in various web and mobile
applications. Retrieving relevant documents from the massive datasets is challenging for a …

Search has become an integral part of Adobe products and users rely on it to learn about
tool usage, shortcuts, quick links, and ways to add creative effects and to find assets such as …

Existing search engines use keyword matching or tf-idf based matching to map the query to
the web-documents and rank them. They also consider other factors such as page rank …

The latest advancements in machine learning and deep learning have brought forth the
concept of semantic similarity, which has proven immensely beneficial in multiple …

This paper proposes a novel model that incorporates word semantics into information
retrieval, enabling a whole new range of semantic based retrieval applications. Concepts …

Adopting semantic technologies has proven several benefits for enabling a better
representation of the data and empowering reasoning capabilities over it. However, there …

Semantic Search regroups a set of techniques designed to improve traditional document or
knowledge base search. Semantic Search aims at better grasping the context and the …

Search engines are being extensively used by Mobile App Stores, where millions of users
world-wide use them every day. However, some stores still resort to simple lexical-based …