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Bisociative Literature-Based Discovery

Bisociative Literature-Based Discovery

0 - Default Title
Description
This monograph introduces the field of bisociative literature-based discovery (LBD) by first explaining the underlying LBD principles and techniques, followed by the presentation of bisociative LBD techniques and applications developed by the authors. LBD is a process of uncovering new knowledge by analyzing and connecting disparate pieces of information from different sources of literature. Selected techniques include conventional natural language processing (NLP) approaches, as well as outlier-based, concept-based, network-based, and embeddings-based LBD approaches. Reproducibility aspects of bisociative LBD research are also covered, addressing all steps of the bisociative LBD process: data acquisition, text preprocessing, hypothesis discovery, and evaluation. The monograph is targeted at researchers, students, and domain experts interested in knowledge exploration, information retrieval, text mining, data science or semantic technologies. By covering texts, relations, networks, and ontologies, this work empowers domain experts to transcend their knowledge silos when confronted with varied data formats in their research practice. The monograph’s open science approach with tutorials in Python allows for code reuse and experiment replicability.
Product details
Number of Pages:
188
Release Date:
2025-08-08
Publication Date:
2025-08-08
Publisher:
Springer
Languages:
Original: English
ISBN10:
303196862X
ISBN13:
9783031968624
GPSR Manufacturer Reference:
[email protected]
Weight:
451 g
Height:
160 cm
Width:
241 cm
Thickness:
16 cm
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