most citedSeed Word Selection for Weakly-Supervised Text Classification with Unsupervised Error Estimation

2 citations · 3 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL20212 cited

Seed Word Selection for Weakly-Supervised Text Classification with Unsupervised Error Estimation

Yiping Jin, Akshay Bhatia, Dittaya Wanvarie

Weakly-supervised text classification aims to induce text classifiers from only a few user-provided seed words. The vast majority of previous work assumes high-quality seed words a…

cs.IR20211 cited

Bootstrapping Large-Scale Fine-Grained Contextual Advertising Classifier from Wikipedia

Yiping Jin, Vishakha Kadam, Dittaya Wanvarie

Contextual advertising provides advertisers with the opportunity to target the context which is most relevant to their ads. However, its power cannot be fully utilized unless we ca…

cs.CL2021

Toward Improving Coherence and Diversity of Slogan Generation

Yiping Jin, Akshay Bhatia, Dittaya Wanvarie +1

Previous work in slogan generation focused on utilising slogan skeletons mined from existing slogans. While some generated slogans can be catchy, they are often not coherent with t…

cs.CL2019

Learning Only from Relevant Keywords and Unlabeled Documents

Nontawat Charoenphakdee, Jongyeong Lee, Yiping Jin +2

We consider a document classification problem where document labels are absent but only relevant keywords of a target class and unlabeled documents are given. Although heuristic me…

cs.LG2019

Lukthung Classification Using Neural Networks on Lyrics and Audios

Kawisorn Kamtue, Kasina Euchukanonchai, Dittaya Wanvarie +1

Music genre classification is a widely researched topic in music information retrieval (MIR). Being able to automatically tag genres will benefit music streaming service providers…