arXiv subjects

Daniel Sonntag

Publications and source records attributed to Daniel Sonntag.

75 records · Page 5Linked to original sources

arXiv2013

Towards a New Science of a Clinical Data Intelligence

In this paper we define Clinical Data Intelligence as the analysis of data generated in the clinical routine with the goal of improving patient care. We define a science of a Clinical Data Intelligence as a data analysis that permits the derivation of scientific, i.e., generalizable and reliable results. We argue that a science of a Clinical Data Intelligence is sensible in the context of a Big Data analysis, i.e., with data from many patients and with complete patient information. We discuss that Clinical Data Intelligence requires the joint efforts of knowledge engineering, information extraction (from textual and other unstructured data), and statistics and statistical machine learning. We describe some of our main results as conjectures and relate them to a recently funded research project involving two major German university hospitals.

cs.CY↗

arXiv2009

Macrodynamics of users' behavior in Information Retrieval

We present a method to geometrize massive data sets from search engines query logs. For this purpose, a macrodynamic-like quantitative model of the Information Retrieval (IR) process is developed, whose paradigm is inspired by basic constructions of Einstein's general relativity theory in which all IR objects are uniformly placed in a common Room. The Room has a structure similar to Einsteinian spacetime, namely that of a smooth manifold. Documents and queries are treated as matter objects and sources of material fields. Relevance, the central notion of IR, becomes a dynamical issue controlled by both gravitation (or, more precisely, as the motion in a curved spacetime) and forces originating from the interactions of matter fields. The spatio-temporal description ascribes dynamics to any document or query, thus providing a uniform description for documents of both initially static and dynamical nature. Within the IR context, the techniques presented are based on two ideas. The first is the placement of all objects participating in IR into a common continuous space. The second idea is the `objectivization' of the IR process; instead of expressing users' wishes, we consider the overall IR as an objective physical process, representing the IR process in terms of motion in a given external-fields configuration. Various semantic environments are treated as various IR universes.

cs.IR↗

arXiv2009

On Introspection, Metacognitive Control and Augmented Data Mining Live Cycles

We discuss metacognitive modelling as an enhancement to cognitive modelling and computing. Metacognitive control mechanisms should enable AI systems to self-reflect, reason about their actions, and to adapt to new situations. In this respect, we propose implementation details of a knowledge taxonomy and an augmented data mining life cycle which supports a live integration of obtained models.

cs.AI↗