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- Adapting ranking SVM to document retrieval599
Experimental results show that the modifications made in conventional Ranking SVM can outperform the conventional ranking SVM and other existing methods for document retrieval on two datasets and employ two methods to conduct optimization on the loss function: gradient descent and quadratic programming.
- Low-Quality Product Review Detection in Opinion Summarization424
Experimental results show that the proposed approach effectively discriminates lowquality reviews from high-quality ones and enhances the task of opinion summarization by detecting and filtering low quality reviews.
- Email data cleaning171
A cascaded approach is proposed, which cleans up an email in four passes including non-text filtering, paragraph normalization, sentence normalization, and word normalization, which becomes independent from any specific text mining processing.
- Searching Questions by Identifying Question Topic and Question Focus170
Experimental results indicate that the approach of identifying question topic and question focus for search significantly outperforms the baseline methods such as Vector Space Model (VSM) and Language Model for Information Retrieval (LMIR).
- Understanding and summarizing answers in community-based question answering services125
An in-depth analysis of questions and answers on cQA services finds that the assumption that questions always have unique best answers cannot be true, and shows that question-type oriented summarization techniques can improve cZA answer quality significantly.
- Read, Listen, and See: Leveraging Multimodal Information Helps Chinese Spell Checking118
The ReaLiSe model tackles the CSC task by capturing the semantic, phonetic and graphic information of the input characters, and selectively mixing the information in these modalities to predict the correct output.
- Research on Expert Search at Enterprise Track of TREC 2006118
In this research, a new evidence-oriented framework to expert search is proposed, whereby the task of Expert Search can be accomplished in three steps, namely, 1) evidence extraction, 2) evidence quality evaluation, and 3) evidence merging.
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- Base Noun Phrase translation using web data and the EM algorithm116
Experimental results indicate that the coverage and accuracy of the method are significantly better than those of the baseline methods relying on existing technologies.
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- Making Large Language Models Better Reasoners with Alignment94
The constraint alignment loss has two objectives: a) Alignment, which guarantees that positive scores surpass negative scores to encourage answers with high-quality COTs, and b) Constraint, which keeps the negative scores confined to a reasonable range to prevent the model degradation.
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- An Enhanced Span-based Decomposition Method for Few-Shot Sequence Labeling73
SD decomposes the span matching problem into a series of span-level procedures, mainly including enhanced span representation, class prototype aggregation and span conflicts resolution, which achieves the new state-of-the-art results on two popular FSSL benchmarks, FewNERD and SNIPS.
- Asking Effective and Diverse Questions: A Machine Reading Comprehension based Framework for Joint Entity-Relation Extraction70
This paper improves the existing MRC-based entity-relation extraction model through diverse question answering and significantly outperforms baseline models, which improves the relation F1 to 62.1% on ACE05 and 71.9% on CoNLL04.
- Knowledge-Sensed Cognitive Diagnosis for Intelligent Education Platforms68
A Knowledge-Sensed Cognitive Diagnosis (KSCD) framework is proposed, aiming at learning intrinsic relations among knowledge concepts from student response logs and incorporating them for inferring students' mastery over all knowledge concepts in an end-to-end manner.
- Recommending questions using the mdl-based tree cut model68
Experimental results indicate that the use of the MDL-based tree cut model can significantly outperform the baseline methods of word- based VSM or phrase-based VSM.
- Title extraction from bodies of HTML documents and its application to web page retrieval67
Experimental results indicate that the use of both extracted titles and title fields is almost always better than theuse of title fields alone; theUse of extracted titles is particularly helpful in the task of named page finding.
- Seeking Patterns, Not just Memorizing Procedures: Contrastive Learning for Solving Math Word Problems62
This paper investigates how a neural network understands patterns only from semantics, and proposes a contrastive learning approach, where the neural network perceives the divergence of patterns.
- Collective Tweet Wikification based on Semi-supervised Graph Regularization59
A novel semi-supervised graph regularization model is proposed to incorporate both local and global evidence from multiple tweets through three fine-grained relations in order to identify semanticallyrelated mentions for collective inference.
- Ranking definitions with supervised learning methods59
Experimental results indicate that the use of SVM and Ranking SVM can significantly outperform the baseline methods of using heuristic rules or employing the conventional information retrieval method of Okapi, indicating that generic models for definition ranking can be constructed.
- Enhancing Label Correlation Feedback in Multi-Label Text Classification via Multi-Task Learning54
This work introduces a novel approach with multi-task learning to enhance label correlation feedback and proposes two auxiliary label co-occurrence prediction tasks to enhancelabel correlation learning.
- Improving BERT with Syntax-aware Local Attention52
A syntax-aware local attention, where the attention scopes are restrained based on the distances in the syntactic structure is proposed, which can be integrated with pretrained language models, such as BERT, to render the model to focus on syntactically relevant words.
- Dialogue Response Selection with Hierarchical Curriculum Learning51
A hierarchical curriculum learning framework that trains the matching model in an “easy-to-difficult” scheme for dialogue response selection significantly improves the model performance across various evaluation metrics.
- Web page title extraction and its application50
Experimental results indicate that the use of both extracted titles and title fields is almost always better than theuse of title fields alone; the useof extracted titles is particularly helpful in the task of named page finding.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-15. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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