Effective Citation Recommendation by Unbiased Reference Priority Recognition

Lu, Wen-Yang; Yang, Yu-Bin; Mao, Xu; Zhu, Qi-Hai

doi:10.1007/978-3-319-25255-1_44

Cited by 2 publications

(2 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…2.1 for the distinction between local and global citation recommendation). This means that only 33.3% of the approaches SIGIR'07 Nallapati et al [113] KDD'08 Tang et al [144] PAKDD'09 He et al [68] WWW'10 Kataria et al [85] AAAI'10 Bethard et al [19] CIKM'10 He et al [67] WSDM'11 Lu et al [101] CIKM'11 Wu et al [159] FSKD'12 He et al [65] SPIRE'12 Huang et al [70] CIKM'12 Rokach et al [127] LSDS-IR'13 Liu et al [97] AIRS'13 Jiang et al [80] TCDL Bulletin'13 Zarrinkalam et al [167] Program'13 Duma et al [41] ACL'14 Livne et al [99] SIGIR'14 Tang et al [146] SIGIR'14 Ren et al [124] KDD'14 Liu et al [95] JCDL'14 Liu et al [94] CIKM'14 Jiang et al [81] Web-KR'14 Huang et al [71] WCMG'15 Chakraborty et al [34] ICDE'15 Hsiao et al [69] MDM'15 Gao et al [56] FSKD'15 Lu et al [100] APWeb'15 Jiang et al [82] CIKM'15 Liu et al [96] iConf'16 Duma et al [43] LREC'16 Duma et al [42] D-Lib'16 Yin et al [166] APWeb'17 Ebesu et al [44] SIGIR'17 Guo et al [61] IEEE'17 Cai et al [28] AAAI'18 Bhagavatula et al [20] NAACL'18 Kobayashi et al [87] JCDL'18 Jiang et al [83] JCDL'18 Han et al [63] ACL'18 Jiang et al [84] SIGIR'18 Zhang et al [168] ISMIS'18 Cai et al <...>…”

Section: Corpus Creationmentioning

confidence: 99%

See 1 more Smart Citation

Citation Recommendation: Approaches and Datasets

Färber,

Jatowt

2020

Preprint

View full text Add to dashboard Cite

Citation recommendation describes the task of recommending citations for a given text. Due to the overload of published scientific works in recent years on the one hand, and the need to cite the most appropriate publications when writing scientific texts on the other hand, citation recommendation has emerged as an important research topic. In recent years, several approaches and evaluation data sets have been presented. However, to the best of our knowledge, no literature survey has been conducted explicitly on citation recommendation. In this article, we give a thorough introduction into automatic citation recommendation research. We then present an overview of the approaches and data sets for citation recommendation and identify differences and commonalities using various dimensions. Last but not least, we shed light on the evaluation methods, and outline general challenges in the evaluation and how to meet them. We restrict ourselves to citation recommendation for scientific publications, as this document type has been studied the most in this area. However, many of the observations and discussions included in this survey are also applicable to other types of text, such as news articles and encyclopedic articles.

show abstract

Section: Corpus Creationmentioning

confidence: 99%

“…Classification of citation recommendation approaches based on their set-up. The approaches are classified as follows: A:[104,124,81,82,69,34,56,100,61,20,83,84,28,27,163,37,112,161,29]: B:[19]; C:[167]; D:[137,113,144,159,80,94,96,43,42,168,38,101,95]; E:[68,67,70,127,97,41,146,71,166,44,162,77]; F:…”

mentioning

confidence: 99%

Citation Recommendation: Approaches and Datasets

Färber,

Jatowt

2020

Preprint

View full text Add to dashboard Cite

show abstract

Citation recommendation: approaches and datasets

Färber

Jatowt

2020

Int J Digit Libr

View full text Add to dashboard Cite

Citation recommendation describes the task of recommending citations for a given text. Due to the overload of published scientific works in recent years on the one hand, and the need to cite the most appropriate publications when writing scientific texts on the other hand, citation recommendation has emerged as an important research topic. In recent years, several approaches and evaluation data sets have been presented. However, to the best of our knowledge, no literature survey has been conducted explicitly on citation recommendation. In this article, we give a thorough introduction to automatic citation recommendation research. We then present an overview of the approaches and data sets for citation recommendation and identify differences and commonalities using various dimensions. Last but not least, we shed light on the evaluation methods and outline general challenges in the evaluation and how to meet them. We restrict ourselves to citation recommendation for scientific publications, as this document type has been studied the most in this area. However, many of the observations and discussions included in this survey are also applicable to other types of text, such as news articles and encyclopedic articles.

show abstract

Effective Citation Recommendation by Unbiased Reference Priority Recognition

Cited by 2 publications

References 18 publications

Citation Recommendation: Approaches and Datasets

Citation Recommendation: Approaches and Datasets

Citation recommendation: approaches and datasets

Contact Info

Product

Resources

About