Geoffrey I. Webb, Jason Wells, and Zijian Zheng. An Experimental Evaluation of Integrating Machine Learning with Knowledge Acquisition. Machine  Home/Search   Document Details and Download   Summary   Related Articles   Check

....to select the correct ones from the generated ones. This system also maintains connections between rules and the examples they explain, making knowledge maintenance easier. Some work has also looked at interleaving machine learning and knowledge acquisition to make knowledge acquisition easier [45, 51, 38]. However, current systems still construct knowledge acquisition interfaces for contributors that need to be trained in using these tools. Out proposed work seeks to change this, enabling collection in plain English from untrained users. 2.5 NLP: text mining and question answering The advent of ....

G. I. Webb, J. Wells, and Z. Zheng. An experimental evaluation of integrating machine learning with knowledge acquisition. Machine Learning, 35:5, 1999.

....with over the last two decades when they elaborated on methodologies for knowledge acquisition or workbenches for defining knowledge bases. A method that proved extremely beneficial for the knowledge acquisition task was the integration of knowledge acquisition with machine learning techniques [10]. The drawback of these approaches, e.g. the work described in [5] however, was their rather strong focus on structured knowledge or data bases, from which they induced their rules. In contrast, in the Web environment that we encounter when building Web ontologies, the structured knowledge or ....

.... Staab [14] Frequency based Syntax Prune Kietz et al. 13] Pattern Matching Extract Morin [15] Classification Syntax, Semantics Refine Schnattinger Hahn [8] Dictionary Information extraction Syntax Extract Hearst [9] Wilks [21] and Kietz et al. 13] Page rank Tokens Jannink Wiederhold [10] Knowledge base Concept Induction, A Box mining Relations Extract Kietz Morik [12] and Schlobach [18] Semistructured schemata Naive Bayes Relations Reverse engineering Doan et al. 4] Relational schemata Data Correlation Relations Reverse engineering Johannesson [11] and Tari et ....

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G. Webb, J. Wells, and Z. Zheng. An experimental evaluation of integrating machine learning with knowledge acquisition. Machine Learning, 35(1), 1999. 19

....the value of being an experimental science. Some sub#elds of AI have developed standard tasks and test sets that are used routinely by researchers to show new results. Researchers in machine learning, for example, use the Irvine data sets to show improvements in inductive learning #Quinlan, 1993; Webb et al. 1999# and routinely use tasks like the n puzzle or the n queens for speed up learning research#Tambe Rosenbloom, 1990; Kim Rosenbloom, 1996#. Developing standard tests is harder in other sub#elds that address more knowledge intensive problems. For example, planning researchers often show ....

Webb, G. I., Wells, J., & Zheng, Z. #1999#. An experimental evaluation of integrating machine learning with knowledge acquisition. Machine Learning, 35:5#23.

....of 73 ffl When the behaviouralK is small (say, a few hundred examples) manual knowledge acquisition may generate a better KB than inductive ML. 1220 ffl Machine learning techniques are not widely used by knowledge acquisition researchers (though see the short list of integrated ML KA systems in [119]) Roughly speaking, this is because ML research has focused more on general purpose inductive learners than deductive learners since the latter relies on more domain specific modeling assumptions. Hence, ML has 1225 focused on the kind of learning algorithm that is least useful for knowledge ....

G.I. Webb and J. Wells. Experimental Evaluation of Integrating Machine Learning with Knowledge Acquisition Through Direct Interaction with Domain Experts. In Proceed- 1640 ings PKAW '96: Pacific Knowledge Acquisition Workshop, 1996.

....1330 ffl When the behaviouralK is small (say, a few hundred examples) manual knowledge acquisition may generate a better KB than inductive ML. ffl Machine learning techniques are not widely used by knowledge acquisition researchers (though see the short list of integrated ML KA systems in [126]) Roughly speaking, this is because ML research has focused more on 1335 general purpose inductive learners than deductive learners since the latter relies on more domain specific modeling assumptions. Hence, ML has focused on the kind of learning algorithm that is least useful for knowledge ....

G.I. Webb and J. Wells. Experimental Evaluation of Integrating Machine Learning with Knowledge Acquisition Through Direct Interaction with Domain Experts. In Proceedings PKAW '96: Pacific Knowledge Acquisition Workshop, 1996.

....combined approach being more effective than either of its components. However, although there have been case studies documenting successful applications of these integrated techniques (Buntine Stirling, 1991; Morik, Wrobel, Kietz, Emde, 1993; Nedellec, Correia, Ferreira, Costa, 1994; Webb, 1996), no previous research has provided comparative evaluation of the relative merits of integrated approaches as opposed to either constituent approach on its own. In particular, it has not been demonstrated that integration of machine learning with knowledge acquisition can outperform with respect ....

....developed by knowledge acquisition alone and examined the effects of using machine learning for its further refinement. It remains unclear how refining the initial expert system using conventional knowledge acquisition without machine learning would have fared had equivalent effort been expended. Webb (1996) describes a case study in which undergraduate computer science students used The Knowledge Factory to produce expert systems for an artificial medical domain. Evaluation of questionnaires administered on completion of the project revealed that the students found the system easy to use, regarded ....

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Webb, G. I., & Wells, J. (1996). Experimental evaluation of integrating machine learning with knowledge acquisition through direct interaction with domain experts. Proceedings of the Pacific Knowledge Acquisition Workshop (pp. 170--189). Sydney, Australia.

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Geoffrey I. Webb, Jason Wells, and Zijian Zheng. An Experimental Evaluation of Integrating Machine Learning with Knowledge Acquisition. Machine

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