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II abstract structure

The following points provide guidance for writing annotations. As appropriate each of these issues might be assessed and commented on in the annotation.

Introduction (background information)

1

Introduce the study by describing the context.

Explain why the subject is important.

e.g. In order to reduce costs, Thompson Consulting needs to find an alternative material for a top-secret military jet engine.

Qualifications of author(s) (if available)

2

Qualifications of the author, unless very well known, should be clearly stated. Preferably this is to be done early in the annotation.

e.g. ‘Based on 20 years of study, William A. Smith, professor of English at Leeds University…’

Outline of major thesis, theories and ideas (purpose, scope)

3

What is the author's reason for writing?

Does the author state a purpose for doing the research and/or writing the piece? If not, can the purpose be inferred?

e.g. Tim Berners Lee played a key role in the development of World Wide Web.

Major bias or standpoint of the author

4

What the author’s opinion concerning the main idea?

e.g. The text focuses on a distinctive group of engineers and entrepreneurs who improved the designs of computer technology and found ways to make the computer more attractive to people.

Methods (ways of investigation)

5

What method of obtaining data or conducting research was employed by the author?

e.g. Researchers conducted speed tests on the new quantum computer that was supposed to solve billions operations a second.

Results (if available)

6

What are the consequences of the problem or issue

that the author is discussing?

Report the results that were found.

e.g. Pre-training program scores of 385 on the LSAT and 750 on the combined GRE climbed to 435 and 895 respectively.

Relationship to other works in this field (if available)

7

How does the research result compare with similar studies?

Are all similar studies cited by the author?

e.g. The approach, findings and conclusions were similar to those of Henley in Anodic Oxidation of Aluminum and Its Alloys (Elsevier Science Ltd, 1982)

The intended audience and level of reading difficulty.

8

Does the piece have an intended audience?

This is not always present in an annotation but is important if the work is targeted to a specific audience.

e.g. Schmidt addresses himself to the scholar, but the concluding chapters will be clear to any computer user.

Conclusion

9

What conclusions does the author draw from his/her study of the issue or problem?

Are the conclusions in line with the original purpose of the research?

e.g. This research will move our understanding forward of how brains work, and could have a profound effect on many areas of science and medicine.

Special features (if available)

10

Bibliography, glossary, index, survey, instruments, testing devices, etc.

e.g. A short list of readings is appended.

TASK 2 Read the annotation in italics and study its elements.

"Access-Limited Logic -- A Language for Knowledge Representation." The University of Texas at Austin, Department of Computer Sciences. AI Technical Report 90-141. October 1990. 237 pages.

Hermjakob, Ph.D.

Qualifications of author

Access-Limited Logic (ALL) is a language for knowledge representation which formalizes the access limitations inherent in a network structured knowledge-base.

Introduction

Where a deductive method such as resolution would retrieve all assertions that satisfy a given pattern, an access-limited logic retrieves all assertions reachable by following an available access path.

Outline of major thesis, theories and ideas

(purpose and scope)

The time complexity of inference is thus a polynomial function of the size of the accessible portion of the knowledge- base, rather than the size of the entire knowledge-base. Access-Limited Logic, though incomplete, still has a well defined semantics and a weakened form of completeness, Socratic Completeness, which guarantees that for any query which is a logical consequence of the knowledge-base, there exists a series of queries after which the original query will succeed.

Major bias, standpoint of the author

We have implemented ALL in Lisp and it has been used to build several non-trivial systems, including versions of Qualitative Process Theory and Pearl's probability networks.

Methods (ways of investigation)

ALL is a step toward providing the properties - clean semantics, efficient inference, expressive power - which will be necessary to build large, effective knowledge bases.

Conclusion

TASK 3 Read carefully the annotation from the field of computer assisted learning. What structure elements from the table above do the sentences 1-7 refer to?

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