Mapping Local News Coverage: Precise location extraction in textual news content using fine-tuned BERT based language model
Mapping local news coverage from textual content is a challenging problem that requires extracting precise location mentions from news articles. While traditional named entity taggers are able to extract geo-political entities and certain non geo-political entities, they cannot recognize precise location mentions such as addresses, streets and intersections that are required to accurately map the news article. We fine-tune a BERT-based language model for achieving high level of granularity in location extraction. We incorporate the model into an end-to-end tool that further geocodes the extracted locations for the broader objective of mapping news coverage.
Code (0)
등록된 구현이 없습니다.
Tasks
ArticlesLanguage ModelingLanguage ModellingSimilar Papers 제목 키워드 기반
Beyond the Surface: Uncovering Implicit Locations with LLMs for Personalized Local News
News recommendation systems personalize homepage content to boost engagement, but factors like content type, editorial stance, and geographic focus impact recommendations. Local newspapers balance coverage across regions…
ArticlesClassificationKnowledge Graphsnamed-entity-recognition+5Mobile Coverage Analysis using Crowdsourced Data
Effective assessment of mobile network coverage and the precise identification of service weak spots are paramount for network operators striving to enhance user Quality of Experience (QoE). This paper presents a novel f…
What's happening in your neighborhood? A Weakly Supervised Approach to Detect Local News
Local news articles are a subset of news that impact users in a geographical area, such as a city, county, or state. Detecting local news (Step 1) and subsequently deciding its geographical location as well as radius of …
ArticlesNERNews RecommendationDoes Local News Stay Local?: Online Content Shifts in Sinclair-Acquired Stations
Local news stations are often considered to be reliable sources of non-politicized information, particularly local concerns that residents care about. Because these stations are trusted news sources, viewers are particul…
AI-Augmented Density-Driven Optimal Control (D2OC) for Decentralized Environmental Mapping
This paper presents an AI-augmented decentralized framework for multi-agent (multi-robot) environmental mapping under limited sensing and communication. While conventional coverage formulations achieve effective spatial …