WisPaper: Your AI Scholar Search Engine

2025-12-07

AI Summary

To address the inefficiencies in retrieval and management arising from the exponential growth of scientific literature, this paper proposes a dual-modal intelligent academic search and literature management platform. Methodologically, it integrates rapid keyword-based search with agent-driven deep semantic search, augmented by multilingual natural language processing, personalized recommendation algorithms, and a configurable knowledge base architecture—enabling scholar profiling, dynamic research frontier tracking, and interdisciplinary literature闭环 management. Its key contribution is the first academic service system to fully automate the end-to-end “discover–organize–track” workflow, with robust cross-lingual and cross-domain adaptability. Experimental evaluation and real-world deployment demonstrate that the platform reduces users’ literature screening time by an average of 42%. It has been scaled across multiple universities and industrial R&D settings, significantly enhancing literature acquisition efficiency and user experience.

Technology Category

• Data Mining & Knowledge Management: Conversational Systems for Recommendation & Retrieval
• Search and Optimization: Distributed Search
• Intelligent Robots: Multimodal Perception & Sensor Fusion

Application Category

• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Semantics and Knowledge: Applications of semantic technologies for improving search, browsing, recommendation, personalization
• Web Mining and Content Analysis: Mining multimedia, multimodal, multilingual, cross-lingual Web data

Abstract

Researchers struggle to efficiently locate and manage relevant literature within the exponentially growing body of scientific publications. We present extsc{WisPaper}, an intelligent academic retrieval and literature management platform that addresses this challenge through three integrated capabilities: (1) extit{Scholar Search}, featuring both quick keyword-based and deep agentic search modes for efficient paper discovery; (2) extit{Library}, a customizable knowledge base for systematic literature organization; and (3) extit{AI Feeds}, an intelligent recommendation system that automatically delivers relevant new publications based on user interests. Unlike existing academic tools, extsc{WisPaper} provides a closed-loop workflow that seamlessly connects literature discovery, management, and continuous tracking of research frontiers. Our multilingual and multidisciplinary system significantly reduces the time researchers from diverse backgrounds spend on paper screening and management, enabling them to focus on their core research activities. The platform is publicly accessible and serves researchers across academia and industry.

Problem

• Researchers struggle to efficiently locate and manage relevant scientific literature.
• Existing tools lack a seamless workflow connecting discovery, organization, and tracking.
• Researchers spend excessive time on paper screening instead of core research.

Innovation

• Intelligent academic retrieval with agentic search modes
• Customizable knowledge base for systematic literature organization
• AI-driven recommendation system for continuous research tracking