skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: CiteSeerX: 20 years of service to scholarly big data
We overview CiteSeerX, the pioneer digital library search engine, that has been serving academic communities for more than 20 years (first released in 1998), from three perspectives. The system perspective summarizes its architecture evolution in three phases over the past 20 years. The data perspective describes how CiteSeerX has created searchable scholarly big datasets and made them freely available for multiple purposes. In order to be scalable and effective, AI technologies are employed in all essential modules. To effectively train these models, a sufficient amount of data has been labeled, which can then be reused for training future models. Finally, we discuss the future of CiteSeerX. Our ongoing work is to make Cite- SeerX more sustainable. To this end, we are working to ingest all open access scholarly papers, estimated to be 30-40 million. Part of the plan is to discover dataset mentions and metadata in scholarly articles and make them more accessible via search interfaces. Users will have more opportunities to explore and trace datasets that can be reused and discover other datasets for new research projects. We summarize what was learned to make a similar system more sustainable and useful.  more » « less
Award ID(s):
1823288
PAR ID:
10173327
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Proceedings of the Conference on Artificial Intelligence for Data Discovery and Reuse, AIDR 2019
Page Range / eLocation ID:
1:1-1:4
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; (, International Conference on Web Services)
    Scholarly digital libraries provide access to scientific publications and comprise useful resources for researchers who search for literature on specific subject areas. CiteSeerX is an example of such a digital library search engine that provides access to more than 10 million academic documents and has nearly one million users and three million hits per day. Artificial Intelligence (AI) technologies are used in many components of CiteSeerX including Web crawling, document ingestion, and metadata extraction. CiteSeerX also uses an unsupervised algorithm called noun phrase chunking (NP-Chunking) to extract keyphrases out of documents. However, often NP-Chunking extracts many unimportant noun phrases. In this paper, we investigate and contrast three supervised keyphrase extraction models to explore their deployment in CiteSeerX for extracting high quality keyphrases. To perform user evaluations on the keyphrases predicted by different models, we integrate a voting interface into CiteSeerX. We show the development and deployment of the keyphrase extraction models and the maintenance requirements. 
    more » « less
  2. (, Large Scale Networking (LSN) Workshop on Huge Data: A Computing, Networking and Distributed Systems Perspective)
    The volume of scholarly data has been growing exponentially over the last 50 years. The total size of the open access documents is estimated to be 35 million by 2022. The total amount of data to be handled, including crawled documents, production repository, metadata, extracted content, and their replications, can be as high as 350TB. Academic digital library search engines face significant challenges in maintaining sustainable services. We discuss these challenges and propose feasible solutions to key modules in the digital library architecture including the document storage, data extraction, database and index. We use CiteSeerX as a case study. 
    more » « less
  3. (, Large Scale Networking (LSN) Workshop on Huge Data: A Computing, Networking and Distributed Systems Perspective)
    The volume of scholarly data has been growing exponentially over the last 50 years. The total size of the open access documents is estimated to be 35 million by 2022. The total amount of data to be handled, including crawled documents, production repository, metadata, extracted content, and their replications, can be as high as 350TB. Academic digital library search engines face significant challenges in maintaining sustainable services. We discuss these challenges and propose feasible solutions to key modules in the digital library architecture including the document storage, data extraction, database and index. We use CiteSeerX as a case study. 
    more » « less
  4. (, Challenges For Large Scale Networking (LSN) Workshop on Huge Data: A Computing, Networking and Distributed Systems Perspective)
    The volume of scholarly data has been growing exponentially over the last 50 years. The total size of the open access documents is estimated to be 35 million by 2022. The total amount of data to be handled, including crawled documents, production repository, metadata, extracted content, and their replications, can be as high as 350TB. Academic digital library search engines face signi cant challenges in maintaining sustainable services. We discuss these challenges and propose feasible solutions to key modules in the digital library architecture including the document storage, data extraction, database and index. We use CiteSeerX as a case study. 
    more » « less
  5. ; ; ; ; (, Forum for Information Retrieval Evaluation. (FIRE 2022))
    he advancement of web programming techniques, such as Ajax and jQuery, and datastores, such as Apache Solr and Elasticsearch, have made it much easier to deploy small to medium scale web- based search engines. However, developing a sustainable search engine that supports scholarly big data services is still challenging often because of limited human resources and financial support. Such scenarios are typical in academic settings or small businesses. Here, we showcase how four key design decisions were made by trading-off competing factors such as performance, cost, and effi- ciency, when developing the Next Generation CiteSeerX (NGX), the successor of CiteSeerX, which was a pioneering digital library search engine that has been serving academic communities for more than two decades. This work extends our previous work in Wu et al. (2021) and discusses design considerations of infrastruc- ture, web applications, indexing, and document filtering. These design considerations can be generalized to other web-based search engines with a similar scale that are deployed in small business or academic settings with limited resources. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email