TRENDS IN STRUCTURE-ORIENTED ENVIRONMENTS

In today’s knowledge-based economy, having proper expertise is crucial in resolving many tasks. Expertise Finding (EF) is the area of research concerned with matching available experts to given tasks. A standard approach is to input a task description/proposal/paper into an EF system and receive recommended experts as output. Mostly, EF systems operate either via a content-based approach, which uses the text of the input as well as the text of the available experts’ profiles to determine a match, and structure-based approaches, which use the inherent relationship between experts, affiliations, papers, etc. The underlying data representation is fundamentally different, which makes the methods mutually incompatible. However, previous work (Watanabe et al., 2005a) achieved good results by converting content-based data to a structure-representation and using a structure-based approach. The authors posit that the reverse may also hold merit, namely, a content-based approach leveraging structure-based data converted to a content-based representation. This paper compares the authors’ idea to a content only-based approach, demonstrating that their method yields substantially better performance, and thereby substantiating their claim.

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An Historical Perspective of Reward Systems: Lessons Learned from the Scientific Management Era

International Journal of Human Resource Studies ◽

10.5296/ijhrs.v4i4.6605 ◽

2014 ◽

Vol 4 (4) ◽

pp. 127 ◽

Cited By ~ 3

Author(s):

Helene L. Caudill ◽

Constance D. Porter

Keyword(s):

Historical Perspective ◽

Pay For Performance ◽

Reward System ◽

Profit Sharing ◽

Lessons Learned ◽

Scientific Management ◽

Reward Systems ◽

Gain Sharing ◽

Knowledge Based

This paper reveals how similar the reward systems prevalent during the scientific management era are to the rewards systems in use today. Systems popular today, such as profit sharing, gain sharing, skill/knowledge-based pay, merit-based pay/pay for performance, and variable-based pay, were also advocated during the reign of scientific management. The ideas expressed by several key scientific management contributors, including Frederick W. Taylor, Henry L. Gantt, Harrington Emerson, and Frank B and Lillian M. Gilbreth, are detailed. These ideas are compared and contrasted with existing reward systems and their underlying premises. In addition, the lessons learned from the scientific management era as they relate to reward system philosophies of today are presented.

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Expertise Learning and Identification with Information Retrieval

Information Systems and Modern Society ◽

10.4018/978-1-4666-2922-6.ch004 ◽

2012 ◽

pp. 49-65

Author(s):

Neil Rubens ◽

Dain Kaplan ◽

Toshio Okamoto

Keyword(s):

Information Retrieval ◽

Data Representation ◽

Standard Approach ◽

Structure Representation ◽

Knowledge Based ◽

Task Description ◽

Knowledge Based Economy ◽

Expertise Finding

In today’s knowledge-based economy, having proper expertise is crucial in resolving many tasks. Expertise Finding (EF) is the area of research concerned with matching available experts to given tasks. A standard approach is to input a task description/proposal/paper into an EF system and receive recommended experts as output. Mostly, EF systems operate either via a content-based approach, which uses the text of the input as well as the text of the available experts’ profiles to determine a match, and structure-based approaches, which use the inherent relationship between experts, affiliations, papers, etc. The underlying data representation is fundamentally different, which makes the methods mutually incompatible. However, previous work (Watanabe et al., 2005a) achieved good results by converting content-based data to a structure-representation and using a structure-based approach. The authors posit that the reverse may also hold merit, namely, a content-based approach leveraging structure-based data converted to a content-based representation. This paper compares the authors’ idea to a content only-based approach, demonstrating that their method yields substantially better performance, and thereby substantiating their claim.

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KNOWLEDGE PATTERN REPRESENTATION OF CHINESE CHARACTERS

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001488000121 ◽

1988 ◽

Vol 02 (01) ◽

pp. 161-179

Author(s):

PATRICK SHEN-PEI WANG

Keyword(s):

Syntactic Structure ◽

Chinese Language ◽

Semantic Networks ◽

Future Research ◽

Chinese Characters ◽

Automatic Learning ◽

Language Understanding ◽

Structure Representation ◽

Knowledge Based ◽

Resolution Principle

This article discusses some intelligence aspects of Chinese characters. Some basic concepts of two-dimensional pattern representation and artificial intelligence such as semantic networks, forward chaining, deduction and the resolution principle are used to analyze and interpret the syntactic structure, representation, semantics and evolution of Chinese characters. The concept of degrees of ambiguity and the principle of new characters are investigated. It is found that Chinese characters are actually not only artistically elegant and culturally rich but also semantically meaningful and intelligently sound. Finally some topics for future research such as intelligent pattern recognition for Chinese characters, automatic learning and translation, and knowledge-based Chinese language understanding are discussed.

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Foundations of a General Ethics: Selves, Sentient Beings, and Other Responsively Cohesive Structures

Royal Institute of Philosophy Supplement ◽

10.1017/s1358246111000208 ◽

2011 ◽

Vol 69 ◽

pp. 47-66

Author(s):

Warwick Fox

Keyword(s):

Internal Structure ◽

Term Structure ◽

Internal Organization ◽

Social Arrangements ◽

Sentient Beings

Everything we can refer to – physical, biological, psychological, or a human-created entity, institution, activity, or expression of some kind, and whether constituted of brute physical stuff or less tangible complexes of social arrangements, ideas, images, movements, and so on – can be considered in terms of its form of organization or structure. This applies even if what we want to say about these things is that they represent a disorganized or unstructured example of their kind or else that they simply lack any discernible form of internal organization or structure in the sense that their internal structure is undifferentiated or homogenous as opposed to being ‘all over the place’. We therefore live in a world in which everything can be characterized, either positively or negatively, in terms of its form of organization or structure. (The terms ‘form of organization’ and ‘structure’ can be used interchangeably in the context of this paper, although I will tend to use the term ‘structure’ in what follows.)

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X-ray microtomography

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100107058 ◽

1988 ◽

Vol 46 ◽

pp. 998-999

Author(s):

H.W. Deckman ◽

B.F. Flannery ◽

J.H. Dunsmuir ◽

K.D' Amico

Keyword(s):

Computed Tomography ◽

Internal Structure ◽

Imaging Technique ◽

Three Dimensional ◽

Tissue Structure ◽

Individual Element ◽

X Ray ◽

Non Invasive ◽

Panoramic Imaging ◽

Three Dimensional Images

We have developed a new X-ray microscope which produces complete three dimensional images of samples. The microscope operates by performing X-ray tomography with unprecedented resolution. Tomography is a non-invasive imaging technique that creates maps of the internal structure of samples from measurement of the attenuation of penetrating radiation. As conventionally practiced in medical Computed Tomography (CT), radiologists produce maps of bone and tissue structure in several planar sections that reveal features with 1mm resolution and 1% contrast. Microtomography extends the capability of CT in several ways. First, the resolution which approaches one micron, is one thousand times higher than that of the medical CT. Second, our approach acquires and analyses the data in a panoramic imaging format that directly produces three-dimensional maps in a series of contiguous stacked planes. Typical maps available today consist of three hundred planar sections each containing 512x512 pixels. Finally, and perhaps of most import scientifically, microtomography using a synchrotron X-ray source, allows us to generate maps of individual element.

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The internal structure of medullated wool

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100111987 ◽

1984 ◽

Vol 42 ◽

pp. 388-389

Author(s):

Leo Barish

Keyword(s):

Light Microscopy ◽

Internal Structure ◽

Wool Fiber ◽

Guard Hair ◽

Bright Field ◽

Wool Fibers ◽

Thin Skin ◽

Air Pockets

Although most of the wool used today consists of fine, unmedullated down-type fibers, a great deal of coarse wool is used for carpets, tweeds, industrial fabrics, etc. Besides the obvious diameter difference, coarse wool fibers are often medullated.Medullation may be easily observed using bright field light microscopy. Fig. 1A shows a typical fine diameter nonmedullated wool fiber, Fig. IB illustrates a coarse fiber with a large medulla. The opacity of the medulla is due to the inability of the mounting media to penetrate to the center of the fiber leaving air pockets. Fig. 1C shows an even thicker fiber with a very large medulla and with very thin skin. This type of wool is called “Kemp”, is shed annually or more often, and corresponds to guard hair in fur-bearing animals.

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