FALL A. (1996). Reasoning with Taxonomies. PhD thesis, School of Computing Science, Simon Fraser University, Canada.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....Join algorithm for sparse terms. 35 2.13 Meet al..gorithm for sparse terms. 36 2. 14 Fall s sparse term encoding algorithm presented using a syntax and font similar to that used by Fall in [1]. 37 2.15 Graph showing average code length vs. size of ordered set. 38 2.16 Algorithm to generate a derived context inverted index. 39 2.17 Example of data structures used during ....

....length in symbols of the sparse terms passed as an argument. argument in the other term, and takes the meet between pairs of arguments having the same indicies in the two terms. Figure 2. 14 shows Fall s sparse term encoding algorithm and is presented in the same format as that used by Fall in [1]. The algorithm generates codes for an entire partial order P . It encodes elements in the partial order in a topological order so that a member of the partial order is not encoded until all of its parents have been encoded. Let C denote the set of all sparse terms as defined in Figure 2.10. ....

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A. Fall, Reasoning with Taxonomies. PhD thesis, Simon Fraser University, 1996.

....is analyzed in various stages of compilation and execution. Objects are instances of classes organized in a partial order, and their inheritance depends on the temporal order in which the objects are de ned. The idea of formalizing object inheritance in lattice theoretic terms has been proposed by [AKBLN89, Fal90, Fal95, GR80, HN96, McA86, Par87] and others. There has even been considerable interest in further decomposing inheritance graphs into modules that are ecient to query [DH87, HHS95] The LCA operation is central to such object inheritance formalizations, because it is the natural method to resolve object dependence. Analysis ....

Andrew Fall. Reasoning with Taxonomies. PhD thesis, Simon Fraser University, Burnaby, British Columbia, Canada, 1990.

....is analyzed in various stages of compilation and execution. Objects are instances of classes organized in a partial order, and their inheritance depends on the temporal order in which the objects are de ned. The idea of formalizing object inheritance in lattice theoretic terms has been proposed by [1, 18, 19, 23, 25, 29, 32] and others. There has even been considerable interest in further decomposing inheritance graphs into modules that are ecient to query [17, 24] The LCA operation is central to such object inheritance formalizations because it is the natural method to resolve object dependence. Analysis of ....

A. Fall. Reasoning with Taxonomies. PhD thesis, Simon Fraser University, Burnaby, British Columbia, Canada, 1990.

....increases, there CHAPTER 2. RELATED WORK 13 is a growing need to represent them in a form that is amenable to performing operations efficiently. Encoding hierarchies in a manner that permits quick execution of such operations has been a goal in logic programming and other areas of computer science[14]. Many encoding schemes have been proposed such as in Dahl[9, 10] Brew[5] and Ait Kaci, et al. [4] Although those encoding schemes are successful in their particular fields, research is ongoing in the quest for general purpose, compact, flexible and efficient encoding techniques. Interesting ....

A. Fall. Reasoning with taxonomies. Ph.D Thesis, School of Computing Science, Simon Fraser University, 1996.

....: NUM ST LIST FUNC : INTEGER NUM : INTEGER . smallest term . 4 1. 1 12. example term 3. 1 . 3 . example term 2. 2 . 1 . invalid term. a) b) Figure 4. 2: Sparse Terms, a) EBNF for sparse terms, b) Some examples of sparse terms Fall [7] introduced the idea of using sparse terms for encoding taxonomies. Sparse terms representationally subsume some other well studied encoding techniques including bit vectors and integer vectors, logical terms, and interval sets. Fall s encoding algorithm is easily adapted to encode modi cations to ....

Andrew Fall. Reasoning with Taxonomies. PhD thesis, Simon Fraser University, 1996.

....Forms of Partial Orders Conceptual hierarchies are restricted to tree structures which may represent a large amount of partial orders existing in data. However, there are some partial orders in databases which do not form a tree structure. Many studies on general forms of partial orders exist [111, 30]. Our methods can be extended in two ways to deal with general partial orders. ffl A general partial order can be split into several conceptual hierarchies so that one of them is used in a particular data mining session. This is based on the assumption that there are many ways to organize the ....

A. Fall. Reasoning with taxonomies. In Ph.D. Dissertation, Simon Fraser University, Burnaby, B.C., Canada, 1996.

....individuals, introducing course content into concept type hierarchies, etc. Once basic activities are supported, the focus will change to building and supporting concept hierarchies for a test course subject. The concept type hierarchies will based upon Andrew Fall s taxonomy encoding work [12]. Agent development for the concept type hierarchy will come in two forms: guided learning agents and an agent to track student progress. The guided learning agents will allow a student to ask for more information regarding a topic that has been read about (i.e. after reading about a central ....

....related to guided learning, guided reading, directed exploration, etc. Complete testing and code browsing of systems relevant to guided learning. 4 weeks Create a concept type hierarchy of a small, controlled subject domain (i.e. components of a computer) using Andrew Fall s taxonomy encoding work [12]. 2 weeks Design and implement an agent for using the concept type hierarchy to direct a student through a lesson on the chosen topic (i.e. learn the composition of a computer) in LogiMOO. 1 week Examine developments for formalizations and document. 2 weeks Testing by student volunteers at Grande ....

A. Fall. Reasoning With Taxonomies. PhD thesis, School of Computing Science, Simon Fraser University, 1997.

....for efficient subsequent consultation. This is obtained by taxonomic encoding techniques which reduce expensive hierarchical operations to inexpensive set operations [FALL95] We have developed algorithms for the efficient encoding and management of concept classifications in dynamic environments [FALL96b, FALL96c]. 3.2 Natural Language Interface Assumption Grammars[DAHL96, TARA96a] can be used for representing natural language so that it becomes executable (i.e. so that automatic inferences can be made from our description which result in automatic translations between natural language and meaning ....

Andrew Fall. Reasoning with taxonomies. PhD thesis, Simon Fraser University, July 1996.

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FALL A. (1996). Reasoning with Taxonomies. PhD thesis, School of Computing Science, Simon Fraser University, Canada.

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