|
| << vorige | volgende >> |
Tijdschrift beschrijving
Alle jaargangen van het bijbehorende tijdschrift
Alle afleveringen van het bijbehorende jaargang
Alle artikelen van de bijbehorende aflevering
Details van artikel 4 van 10 gevonden artikelen
| Titel: |
Deviation detection in text using conceptual graph interchange format and error tolerance dissimilarity function |
| Auteur: |
Kamaruddin, Siti Sakira Hamdan, Abdul Razak Bakar, Azuraliza Abu Mat Nor, Fauzias |
| Verschenen in: |
Intelligent data analysis |
| Paginering: | Jaargang 16 (2012) nr. 3 pagina's 487-511 |
| Jaar: |
2012-05-09 |
| Inhoud: |
The rapid increase in the amount of textual data has brought forward a growing research interest towards mining text to detect deviations. Specialized methods for specific domains have emerged to satisfy various needs in discovering rare patterns in text. This paper focuses on a graph-based approach for text representation and presents a novel error tolerance dissimilarity algorithm for deviation detection. We resolve two non-trivial problems, i.e. semantic representation of text and the complexity of graph matching. We employ conceptual graphs interchange format (CGIF) – a knowledge representation formalism to capture the structure and semantics of sentences. We propose a novel error tolerance dissimilarity algorithm to detect deviations in the CGIFs. We evaluate our method in the context of analyzing real world financial statements for identifying deviating performance indicators. We show that our method performs better when compared with two related text based graph similarity measuring methods. Our proposed method has managed to identify deviating sentences and it strongly correlates with expert judgments. Furthermore, it offers error tolerance matching of CGIFs and retains a linear complexity with the increasing number of CGIFs. |
| Uitgever: |
IOS Press |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 4 van 10 gevonden artikelen
| << vorige | volgende >> |