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Liangjie Xu

dblp:27/93 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Databases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Information retrieval · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval › cross-language information retrieval
chinese text retrieval		 0.011997
Chinese Text Retrieval Without Using a Dictionary · SIGIR 1997

Methods — techniques the papers use, named apart from their topics

statistical word segmentation · 0.0bigram indexing · 0.0
YearPublicationVenuePosition
2018 Sensor-based risk perception ability network design for drivers in snow and ice environmental freeway: a deep learning and rough sets approach
Wei Zhao 0017, Liangjie Xu, Jing Bai 0003, Menglu Ji, Troy Runge
 Soft Comput.2
1997 Chinese Text Retrieval Without Using a Dictionary
abstract
It is generafly believed that words, rather than characters, should be the smallest indexing unit for Chinese text retrieval systems, and that it is essential to have a comprehensive Chinese dictionary or lexicon for Chhmse text retrieval systems to do well.Chinese text has no delimiters to mark woni boundaries.As a result, any text retrieval systems that build word-based indexes need to segment text into words.We implemented several statistical and dictionary-hazed word segmentation methods to study the effect on retrieval effectiveness of different segmentation methods using the TREC-S Chinese test collection and topics.The results show that, for all three sets of queries, the simple bigram indexing and the purely statistical word segmentation perform better than the popular dictionary-based maximum matching method with a dictionary of 138,955 entries.
Aitao Chen, Jianzhang He, Liangjie Xu, Fredric C. Gey, Jason Meggs
 SIGIR3