Combining Linguistic and Spatial Information for Document Analysis
Marco Aiello, Christof Monz, Leon Todoran
Abstract
We present a framework to analyze color documents of complex layout. In addition, no assumption is made on the layout. Our framework combines in a content-driven bottom-up approach two different sources of information: textual and spatial. To analyze the text, shallow natural language processing tools, such as taggers and partial parsers, are used. To infer relations of the logical layout we resort to a qualitative spatial calculus closely related to Allen's calculus. We evaluate the system against documents from a color journal and present the results of extracting the reading order from the journal's pages. In this case, our analysis is successful as it extracts the intended reading order from the document.
Create a lesson
Related papers
SpecCompact: Accelerating LLM Agent Context Compaction with Slot-Parallel Semantic Speculative Verification
Yulu An, Yifei Feng, Xiangyang Yin
Balancing hierarchical representation and quantization: A performance trade-off in text embeddings
Kai Ponel, Marco Polignano, Erasmo Purificato et al.
Persona Perspectives: Adopting Viewpoints Reorganizes Representations in LLMs
Austin C. Kozlowski, Avital Mintz, Madison Lee
Before You Continue: Evaluating Time-Sensitive Safety Awareness in Conversational Assistants
Peidi Dong, Yunze Xiao, Yu-Lin Tsai et al.
LooM: Loop-Invariant Memory for Causal Encoder-Decoder Language Models
Lele Yang, Muxi Diao, Zhonghao Yan et al.
SAUCE: Summary Analysis Using Conversation Entailment
Man-Ling Sung, Hemanth Kandula, Jeff Ma et al.