Jingfei Li
Jingfei Li
jingflatfoxmail.com

  Affiliation history
Bibliometrics: publication history
Average citations per article0.67
Citation Count4
Publication count6
Publication years2014-2017
Available for download4
Average downloads per article155.75
Downloads (cumulative)623
Downloads (12 Months)226
Downloads (6 Weeks)17
SEARCH
ROLE
Arrow RightAuthor only


AUTHOR'S COLLEAGUES
See all colleagues of this author




BOOKMARK & SHARE


6 results found Export Results: bibtexendnoteacmrefcsv

Result 1 – 6 of 6
Sort by:

1 published by ACM
January 2017 ACM Transactions on Intelligent Systems and Technology (TIST) - Special Issue: Mobile Social Multimedia Analytics in the Big Data Era and Regular Papers: Volume 8 Issue 3, April 2017
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 5,   Downloads (12 Months): 117,   Downloads (Overall): 117

Full text available: PDFPDF
In many research and application areas, such as information retrieval and machine learning, we often encounter dealing with a probability distribution that is mixed by one distribution that is relevant to our task in hand and the other that is irrelevant and that we want to get rid of. Thus, ...
Keywords: irrelevant term distribution, mixture distribution, regularization, Relevance feedback, distribution separation method

2 published by ACM
July 2016 SIGIR '16: Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 6,   Downloads (12 Months): 48,   Downloads (Overall): 97

Full text available: PDFPDF
Traditional information retrieval systems rank documents according to their relevance to users' input queries. State of the art commercial search engines (SEs) train ranking models and suggest query refinements by exploiting collective intelligence implicitly using global users' query logs. However, they do not provide an explicit channel for users to ...
Keywords: chat channel, search engine, collective intelligence, information retrieval

3
October 2015 NLPCC 2015: Proceedings of the 4th CCF Conference on Natural Language Processing and Chinese Computing - Volume 9362
Publisher: Springer-Verlag New York, Inc.
Bibliometrics:
Citation Count: 0

Session search aims to improve ranking effectiveness by incorporating user interaction information, including short-term interactions within one session and global interactions from other sessions or other users. While various session search models have been developed and a large number of interaction features have been used, there is a lack of ...
Keywords: Query change, Session features, Collective intelligence

4 published by ACM
August 2015 SIGIR '15: Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 3,   Downloads (12 Months): 35,   Downloads (Overall): 165

Full text available: PDFPDF
The quantum probabilistic framework has recently been applied to Information Retrieval (IR). A representative is the Quantum Language Model (QLM), which is developed for the ad-hoc retrieval with single queries and has achieved significant improvements over traditional language models. In QLM, a density matrix, defined on the quantum probabilistic space, ...
Keywords: quantum language model, density matrix transformation, session track

5
July 2015 IJCAI'15: Proceedings of the 24th International Conference on Artificial Intelligence
Publisher: AAAI Press
Bibliometrics:
Citation Count: 0

Recently, a Quantum Language Model (QLM) was proposed to model term dependencies upon Quantum Theory (QT) framework and successively applied in Information Retrieval (IR). Nevertheless, QLM's dependency is based on co-occurrences of terms and has not yet taken into account the Quantum Entanglement (QE), which is a key quantum concept ...

6 published by ACM
July 2014 SIGIR '14: Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval
Publisher: ACM
Bibliometrics:
Citation Count: 4
Downloads (6 Weeks): 3,   Downloads (12 Months): 26,   Downloads (Overall): 244

Full text available: PDFPDF
Recent research has shown that the performance of search engines can be improved by enriching a user's personal profile with information about other users with shared interests. In the existing approaches, groups of similar users are often statically determined, e.g., based on the common documents that users clicked. However, these ...
Keywords: re-ranking, latent dirichlet allocation, query log, search personalisation



The ACM Digital Library is published by the Association for Computing Machinery. Copyright © 2018 ACM, Inc.
Terms of Usage   Privacy Policy   Code of Ethics   Contact Us