The memory extender personal filing system
CHI '86 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Mechanisms of sentence processing: assigning roles to constituents
Parallel distributed processing: explorations in the microstructure of cognition, vol. 2
A general framework for parallel distributed processing
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
The active badge location system
ACM Transactions on Information Systems (TOIS)
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
The capacity of Convergence-Zone episodic memory
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Human-computer interaction: toward the year 2000
Human-computer interaction: toward the year 2000
Lifestreams: an alternative to the desktop metaphor
Conference Companion on Human Factors in Computing Systems
From complexity to creativity: explorations in evolutionary, autopoietic, and cognitive dynamics
From complexity to creativity: explorations in evolutionary, autopoietic, and cognitive dynamics
Application of Spreading Activation Techniques in InformationRetrieval
Artificial Intelligence Review
Robot: mere machine to transcendent mind
Robot: mere machine to transcendent mind
Learning human-like knowledge by singular value decomposition: a progress report
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Design guidelines for landmarks to support navigation in virtual environments
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Managing gigabytes (2nd ed.): compressing and indexing documents and images
Managing gigabytes (2nd ed.): compressing and indexing documents and images
On Updating Problems in Latent Semantic Indexing
SIAM Journal on Scientific Computing
Truth from trash: how learning makes sense
Truth from trash: how learning makes sense
The teachable language comprehender: a simulation program and theory of language
Communications of the ACM
The character, value, and management of personal paper archives
ACM Transactions on Computer-Human Interaction (TOCHI)
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
The State of Cognitive Systems Engineering
IEEE Intelligent Systems
MyLifeBits: fulfilling the Memex vision
Proceedings of the tenth ACM international conference on Multimedia
Cell assemblies as an intermediate level model of cognition
Emergent neural computational architectures based on neuroscience
Hierarchically Classifying Documents Using Very Few Words
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Linked
Stuff I've seen: a system for personal information retrieval and re-use
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
On Information and Knowledge Representation in the Brain
ICCI '03 Proceedings of the 2nd IEEE International Conference on Cognitive Informatics
The perfect search engine is not enough: a study of orienteering behavior in directed search
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Recommender Systems Research: A Connection-Centric Survey
Journal of Intelligent Information Systems
Vision: A Computational Investigation into the Human Representation and Processing of Visual Information
Soar-RL: integrating reinforcement learning with Soar
Cognitive Systems Research
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Information management systems improve the retention of information in large collections. As such they act as memory prostheses, implying an ideal basis in human memory models. Since humans process information by association, and situate it in the context of space and time, systems should maximize their effectiveness by mimicking these functions. Since human attentional capacity is limited, systems should scaffold cognitive efforts in a comprehensible manner. We propose the Principles of Mnemonic Associative Knowledge (P-MAK), which describes a framework for semantically identifying, organizing, and retrieving information, and for encoding episodic events by time and stimuli. Inspired by prominent human memory models, we propose associative networks as a preferred representation. Networks are ideal for their parsimony, flexibility, and ease of inspection. Networks also possess topological properties--such as clusters, hubs, and the small world--that aid analysis and navigation in an information space. Our cognitive perspective addresses fundamental problems faced by information management systems, in particular the retrieval of related items and the representation of context. We present evidence from neuroscience and memory research in support of this approach, and discuss the implications of systems design within the constraints of P-MAK's principles, using text documents as an illustrative semantic domain.