Papers with web mining

3 papers
Automotive Document Labeling Using Large Language Models (2025.emnlp-industry)

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Challenge: Traditionally, mechanics manually browse lengthy documents to locate component information, a process that is time-consuming and error-prone.
Approach: They propose to use large language models to enrich and unify a component database and use hybrid search to select the most relevant component for a document.
Outcome: The proposed method outperforms baselines based on an expert-annotated dataset and significantly reduces the search space and improves retrieval efficiency.
Knowledge Enhanced Reflection Generation for Counseling Dialogues (2022.acl-long)

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Challenge: Using retrieval and generative methods, we generate responses using commonsense and domain knowledge.
Approach: They propose a pipeline that collects domain knowledge through web mining and a model that incorporates knowledge generated by COMET using soft positional encoding and masked self-attention.
Outcome: The proposed pipeline collects domain knowledge through web mining and incorporates knowledge generated by COMET using soft positional encoding and masked self-attention.
Towards Zero-shot Relation Extraction in Web Mining: A Multimodal Approach with Relative XML Path (2023.findings-emnlp)

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Challenge: Existing methods for zero-shot relation extraction do not take into account relationships between text nodes within and across web pages.
Approach: They propose a new approach for zero-shot relation extraction in web mining that encodes the shortest relative paths in the Document Object Model tree of the web page.
Outcome: The proposed method outperforms the state-of-the-art methods on public benchmarks on semi-structured web pages.

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