Conceptual graph interchange format for mining financial statements

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5589 LNAI, Issue , 2009, Pages 579-586

  Kamaruddin, Siti Sakira ^a,b   Hamdan, Abdul Razak ^b   Bakar, Azuraliza Abu ^b   Mat Nor, Fauzias ^b  

^a UNIVERSITI UTARA MALAYSIA   (Malaysia)

^b UNIVERSITI KEBANGSAAN MALAYSIA   (Malaysia)

Author keywords

Conceptual Graph Interchange Format; Deviation Detection; Information Extraction; Text Mining

Indexed keywords

AUTOMATIC TRANSFORMATIONS; CONCEPTUAL GRAPH; CONCEPTUAL GRAPH INTERCHANGE FORMAT; DEVIATION DETECTION; FINANCIAL PERFORMANCE; FINANCIAL STATEMENTS; ILLUSTRATIVE EXAMPLES; INFORMATION EXTRACTION; INTERCHANGE FORMATS; KNOWLEDGE DISCOVERY; SENTENCE STRUCTURES; TEXT MINING;

BENCHMARKING; FUZZY SETS; INFORMATION ANALYSIS; INTERCHANGES; MINING; ROUGH SET THEORY;

MULTI AGENT SYSTEMS;

EID: 69049101284     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-02962-2_73     Document Type: Conference Paper

References (23)

1. Bukh, P.N., Nielsen, C., Gormsen, P., Mouristen, J.: Disclosure of information on intellectual capital in Danish IPO prospectuses. Accounting Auditing & Accountability Journal 18, 713-732 (2005)
2. Beattie, V., McInnes, B., Fearnley, S.: A Methodology for Analysing and Evaluating Narratives in Annual Reports: A Comprehensive Descriptive Profile and Metrics for Disclosure Quality Attributes. Accounting Forum 28, 205-236 (2004)
3. Beattie, V., Thomson, S.J.: Lifting the lid on the use of content analysis to investigate intelectual capital disclosures. Accounting Forum 31, 129-163 (2007)
4. Flostrand, P.: The sell side - observations on intellectual capital indicators. Journal of Intellectual Capital 7, 457-473 (2006)
5. Qui, X.Y., Srinivasan, P., Street, N.: Exploring the Forecasting Potential of Company Annual Reports. In: American Society for Information Science and Technology (ASIS&T) Annual Meeting, Austin, Texas (2006)
6. Sydserff, R., Weetman, P.: A texture index for evaluating accounting narratives: An alternative to readability formulas. Accounting Auditing & Accountability Journal 12, 459-488(1999)
7. Kosala, R., Blockeel, H.: Web Mining Research: A Survey. ACM Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD) Explorations 2 (2000)
8. Sowa, J.F., Way, E.C.: Implementing a semantic interpreter using conceptual graphs. IBM J. Res. Develop 30, 57-69 (1986)
9. Karalopoulos, A., Kokla, M., Kavouras, M.: Geographic Knowledge Representation Using Conceptual Graphs. In: 7th AGILE Conference of Geographic Information Science, Heraklion, Greece (2004)
10. Hensman, S., Dunnion, J.: Automatically Building Conceptual Graphs using VerbNet and WordNet. In: Proceedings of the 2004 international symposium on Information and communication technologies ISICT 2004(2004)
11. Hill, R., Polovina, S., Beer, M.: From Concepts to Agents: Towards a Framework for Multi-Agent System Modelling. In: Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems (AAMAS 2005), The Netherlands, pp. 1155-1156 (2005)
12. Chu, S., Cesnik, B.: Knowledge representation and retrieval using conceptual graphs and free text document self-organisation technique. International Journal of Medical Informatics 62, 121-133 (2001)
13. Zhou, X., Han, H., Chankai, I., Prestrud, A., Brooks, A.: Approaches to text mining for clinical medical records. In: Proceedings of the 2006 ACM symposium on Applied computing, Dijon, France, pp. 235-239 (2006)
14. Jouve, D., Amghar, Y., Chabbat, B., Pinon, J.-M.: Conceptual framework for document semantic modelling: an application to document and knowledge management in the legal domain. Data & Knowledge Engineering 46, 345-375 (2003)
15. Fürst, F., Trichet, F.: AxiomBased Ontology Matching. In: KCAP 2005, Banff, Alberta Canada (2005)
16. Jonker, C.M., Kremer, R., Leeuwen, P.V., Pan, D., Treur, J.: Mapping visual to textual knowledge representation. Knowledge-Based Systems 18 (2005)
17. Sleator, D., Temperley, D.: Parsing English with a link grammar. In: 3rd Int. Workshop of Parsing Technologies (1993)
18. Zhang, L., Yu, Y.: Learning to Generate CGs from Domain Specific Sentences. In: Delugach, H.S., Stumme, G. (eds.) ICCS 2001. LNCS, vol. 2120, p. 44. Springer, Heidelberg (2001)
19. Suchanek, F.M., Ifrim, G., Weikum., G.: Combining Linguistic and Statistical Analysis to Extract Relations from Web Documents. In: SIGKDD International Conference on Knowledge Discovery and Data Mining (2006)
20. Ounis, I., Pasca, M.: A Promising Retrieval Algorithm For Systems based on the Conceptual Graphs Formalism. In: Proceedings of IDEAS 1998 (1998)
21. Montes-y-Gómez, Gelbukh, A., López-López, A.: Mining the news: trends, associations and deviations. Computación y Sistemas 5 (2001)
22. Zhong, J., Zhu, H., Li, J., Yu, Y.: Conceptual Graph Matching for Semantic Search. In: Proceedings of International Conference on Conceptual Structures (2002)
23. Montes-y-Gómez, M., Gelbukh, A., López-López, A.: Detecting Deviations in Text Collections: An Approach Using Conceptual Graphs. In: Coello Coello, C.A., de Albornoz, Á., Sucar, L.E., Battistutti, O.C. (eds.) MICAI 2002. LNCS, vol. 2313, p. 176. Springer, Heidelberg (2002)