Papers with ranking model
PostAc : A Visual Interactive Search, Exploration, and Analysis Platform for PhD Intensive Job Postings (P19-3)
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| Challenge: | Employers’ low awareness and interest in attracting PhD graduates means that the term “PhD” is rarely used as a keyword in job advertisements. |
| Approach: | They propose an online platform that makes the job market visible to job seekers by analyzing the key factors that identify what an employer is looking for when they hire a highly skilled researcher. |
| Outcome: | The proposed platform makes visible the geographic location, industry sector, job title, working hours, continuity, and wage of the research intensive jobs. |
ComSearch: Equation Searching with Combinatorial Strategy for Solving Math Word Problems with Weak Supervision (2023.eacl-main)
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| Challenge: | Existing weakly-supervised methods for solving math word problems are expensive and time-consuming. |
| Approach: | They propose a weakly-supervised approach to solve math word problems . they propose 'comsearch' algorithm which compresses the search space by excluding mathematically equivalent equations. |
| Outcome: | The proposed algorithm can compress the search space by excluding mathematically equivalent equations. |
Ranking and Sampling in Open-Domain Question Answering (D19-1)
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| Challenge: | Existing approaches focus on positive paragraphs which contain the answer during training, making it disturbed by similar but irrelevant paragraphs during testing. |
| Approach: | They propose a ranking model leveraging the paragraph-question and the paragraph relevance to compute a confidence score for each paragraph. |
| Outcome: | Experiments on three datasets show that the proposed model advances the state of the art. |
Semi-Automatic Construction of Word-Formation Networks (for Polish and Spanish) (L18-1)
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| Challenge: | a semi-automatic method for the construction of derivational networks is proposed . the proposed method is general enough to be adopted for other languages . |
| Approach: | They propose a semi-automatic method for the construction of derivational networks using a sequential pattern mining technique. |
| Outcome: | The proposed method is general enough to be adopted for other languages. |