Combining case based reasoning with neural networks

This paper presents a neural network based technique for mapping problem situations to problem solutions for Case-Based Reasoning (CBR) applications. Both neural networks and CBR are instance-based learning techniques, although neural nets work with numerical data and CBR systems work with symbolic data. This paper discusses how the application scope of both paradigms could be enhanced by the use of hybrid concepts. To make the use of neural networks possible, the problem's situation and solution features are transformed into continuous features, using techniques similar to CBR's definition of similarity metrics. Radial Basis Function (RBF) neural nets are used to create a multivariable, continuous input-output mapping. As the mapping is continuous, this technique also provides generalisation between cases, replacing the domain specific solution adaptation techniques required by conventional CBR. This continuous representation also allows, as in fuzzy logic, an associated membership measure to be output with each symbolic feature, aiding the prioritisation of various possible solutions. A further advantage is that, as the RBF neurons are only active in a limited area of the input space, the solution can be accompanied by local estimates of accuracy, based on the sufficiency of the cases present in that area as well as the results measured during testing. We describe how the application of this technique could be of benefit to the real world problem of sales advisory systems, among others

Combining case based reasoning with neural networks

This paper presents a neural network based technique for mapping problem situations to problem solutions for Case-Based Reasoning (CBR) applications. Both neural networks and CBR are instance-based learning techniques, although neural nets work with numerical data and CBR systems work with symbolic data. This paper discusses how the application scope of both paradigms could be enhanced by the use of hybrid concepts. To make the use of neural networks possible, the problem's situation and solution features are transformed into continuous features, using techniques similar to CBR's definition of similarity metrics. Radial Basis Function (RBF) neural nets are used to create a multivariable, continuous input-output mapping. As the mapping is continuous, this technique also provides generalisation between cases, replacing the domain specific solution adaptation techniques required by conventional CBR. This continuous representation also allows, as in fuzzy logic, an associated membership measure to be output with each symbolic feature, aiding the prioritisation of various possible solutions. A further advantage is that, as the RBF neurons are only active in a limited area of the input space, the solution can be accompanied by local estimates of accuracy, based on the sufficiency of the cases present in that area as well as the results measured during testing. We describe how the application of this technique could be of benefit to the real world problem of sales advisory systems, among others

NGC 4138 - A Case Study in Counterrotating Disk Formation

The Sa(r) galaxy NGC 4138 has been recently found to contain an extensive counterrotating disk which appears to be still forming. Up to a third of the stars in the disk system may be on retrograde orbits. A counterrotating ring of H II regions, along with extended counterrotating H I gas, suggests that the retrograde material has been recently acquired in the gas phase and is still trickling in. Using numerical simulations, we have attempted to model the process by which the counterrotating mass has been accreted by this galaxy. We investigate two possibilities: continuous retrograde infall of gas, and a retrograde merger with a gas-rich dwarf galaxy. Both processes are successful in producing a counterrotating disk of the observed mass and dimensions without heating up the primary significantly. Contrary to our experience with a fiducial cold, thin primary disk, the gas-rich merger works well for the massive, compact primary disk of NGC 4138 even though the mass of the dwarf galaxy is a significant fraction of the mass of the primary disk. Although we have restricted ourselves mainly to coplanar infall and mergers, we report on one inclined infall simulation as well. We also explore the possibility that the H-alpha ring seen in the inner half of the disk is a consequence of counterrotating gas clouds colliding with corotating gas already present in the disk and forming stars in the process.Comment: To appear in ApJ, 21 pages, LaTeX (aaspp4) format, 17 figs (gzipped tar file) also available at ftp://bessel.mps.ohio-state.edu/pub/thakar/cr2/ or at http://www-astronomy.mps.ohio-state.edu/~thakar

Formation of Massive Counterrotating Disks in Spiral Galaxies

We present results of numerical simulations of the formation of a massive counterrotating gas disk in a spiral galaxy. Using a hierarchical tree gravity solver combined with a sticky-particle gas dissipation scheme for our simulations, we have investigated three mechanisms: episodic and continuous gas infall, and a merger with a gas-rich dwarf galaxy. We find that both episodic and continuous gas infall work reasonably well and are able to produce a substantial gas counterrotating disk without upsetting the stability of the existing disk drastically, but it is very important for the gas to be well-dispersed in phase-space and not form concentrated clumps prior to its absorption by the disk galaxy. The initial angular momentum of the gas also plays a crucial role in determining the scale length of the counterrotating disk formed and the time it takes to form. The rate of infall, i.e. the mass of gas falling in per unit time, has to be small enough to preclude excessive heating of the preexisting disk. It is much easier in general to produce a smaller counterrotating disk than it is to produce an extensive disk whose scale length is similar to that of the original prograde disk. A gas-rich dwarf merger does not appear to be a viable mechanism to produce a massive counterrotating disk, because only a very small dwarf galaxy can produce a counterrotating disk without increasing the thickness of the existing disk by an order of magnitude, and the time-scale for this process is prohibitively long because it makes it very unlikely that several such mergers can accumulate a massive counterrotating disk over a Hubble time.Comment: Accepted by ApJ, 22 pages, uuencoded compressed Postscript. 18 Figures (compressed Postscript) available from anonymous ftp at ftp://bessel.mps.ohio-state.edu/pub/thakar/cr1/figs.ps.Z A complete (text+figs) compressed PostScript preprint is also available at ftp://bessel.mps.ohio-state.edu/pub/thakar/cr1/pp.ps.g

Data Mining the SDSS SkyServer Database

An earlier paper (Szalay et. al. "Designing and Mining MultiTerabyte Astronomy Archives: The Sloan Digital Sky Survey," ACM SIGMOD 2000) described the Sloan Digital Sky Survey's (SDSS) data management needs by defining twenty database queries and twelve data visualization tasks that a good data management system should support. We built a database and interfaces to support both the query load and also a website for ad-hoc access. This paper reports on the database design, describes the data loading pipeline, and reports on the query implementation and performance. The queries typically translated to a single SQL statement. Most queries run in less than 20 seconds, allowing scientists to interactively explore the database. This paper is an in-depth tour of those queries. Readers should first have studied the companion overview paper Szalay et. al. "The SDSS SkyServer, Public Access to the Sloan Digital Sky Server Data" ACM SIGMOND 2002.Comment: 40 pages, Original source is at http://research.microsoft.com/~gray/Papers/MSR_TR_O2_01_20_queries.do