Discovering Links between Political Debates and Media

@inproceedings{Juric2013DiscoveringLB,
  title={Discovering Links between Political Debates and Media},
  author={Damir Juric and Laura Hollink and Geert-Jan Houben},
  booktitle={ICWE},
  year={2013}
}
Politics and media are heavily intertwined and both play a role in the discussion on policy proposals and current affairs. However, a dataset that allows a joint analysis of the two does not yet exist. In this paper we take the first step by discovering links between parliamentary debates in a political dataset and newspaper articles in a media dataset. Our approach consists of 3 steps. We first discover topics discussed in the debates. Second, we query a newspaper archive for relevant articles… 

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References

SHOWING 1-10 OF 18 REFERENCES

Linking Archives Using Document Enrichment and Term Selection

It is found that the difference in textual richness of annotations presents a challenge and two approaches are investigated: to enrich sparsely annotated items with textually rich content; and to reduce rich news archive items using term selection.

Bilingual News Clustering Using Named Entities and Fuzzy Similarity

This paper proposes a new approach based on a fuzzy system, with a knowledge base that tries to incorporate the human knowledge about the importance of the named entities category in the news, obtaining better results in a comparable corpus with news in Spanish and English.

Learning to model relatedness for news recommendation

This paper proposes a set of features to characterize relatedness between news articles across four aspects: relevance, novelty, connection clarity, and transition smoothness, and puts forward a learning approach to model relatedness.

A Generative Entity-Mention Model for Linking Entities with Knowledge Base

This paper proposes a generative probabilistic model, called entity-mention model, which can leverage heterogenous entity knowledge (including popularity knowledge, name knowledge and context knowledge) for the entity linking task.

Multimodal Document Alignment : Feature-based Validation to Strengthen Thematic Links

A validation approach of detected alignment links between dialog transcript and discussed documents, in the context of a multimodal document alignment framework of multimedia events (meetings and lectures), proves that the choice of the relevant entailment strategy depends on the types of documents available in the corpus, on their content, and also on the nature of the corpus.

SMU-SIS at TAC 2010 - KBP Track Entity Linking

This paper proposes the two way entity linking approach to reformulate query, disambiguate the entity and link to the relevant KB repository, and developed several entity linking engines to evaluate the solution.

Reading Tea Leaves: How Humans Interpret Topic Models

New quantitative methods for measuring semantic meaning in inferred topics are presented, showing that they capture aspects of the model that are undetected by previous measures of model quality based on held-out likelihood.

Entity Linking: Finding Extracted Entities in a Knowledge Base

This work discusses the key challenges present in this task and presents a high-performing system that links entities using max-margin ranking and summarizes recent work in this area and describes several open research problems.

Linking Entities to a Knowledge Base with Query Expansion

A novel approach to entity linking based on a statistical language model-based information retrieval with query expansion with a strong emphasis on named entities in the local contexts and a positional language model to weigh them differently based on their distances to the query.

Design and use of the Simple Event Model (SEM)