Analyzing Multi-level BOM-Structured Event Data

Multi-level Schema Extraction for Heterogenous Semi-structured Data

Event Extraction for Document-Level Structured Summarization

Event extraction has been well studied for more than two decades, through both the lens of document-level and sentence-level event extraction. However, event extraction methods to date do not yet offer a satisfactory solution to providing concise, structured, document-level summaries of events in news articles. Prior work on document-level event extraction methods have focused on highly specifi...

BOM++, a Semantically Enriched BOM

The Defence Conceptual Modelling Framework (DCMF) is the Swedish Defence Research Agency’s (FOI) proposal to deal with conceptual modelling in the military domain. The vision of the DCMF is to enable composability, interoperability and reuse of knowledge for modelling and simulation. The final products, the conceptual models, are called Mission Space Models (MSMs), following the original CMMS p...

Multi-Level Structured Models for Document-Level Sentiment Classification

In this paper, we investigate structured models for document-level sentiment classification. When predicting the sentiment of a subjective document (e.g., as positive or negative), it is well known that not all sentences are equally discriminative or informative. But identifying the useful sentences automatically is itself a difficult learning problem. This paper proposes a joint two-level appr...

High-Level Synthesis of Structured Data Paths

In this paper we present a genetic scheduling algorithm to support the synthesis of structured data paths with the aim of producing designs with a predictable layout structure and conserving on-chip wiring resources. The data path is organized as architectural blocks (A-block) with local functional unit (FU), memory elements and internal interconnections. The A-blocks are interconnected by a fe...