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Ontology-Based Event Modeling for Semantic Understanding of Chinese News Story Wang Wei, Zhao Dongyan Institute of Computer Science & Technology

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Presentation on theme: "Ontology-Based Event Modeling for Semantic Understanding of Chinese News Story Wang Wei, Zhao Dongyan Institute of Computer Science & Technology"— Presentation transcript:

1 Ontology-Based Event Modeling for Semantic Understanding of Chinese News Story Wang Wei, Zhao Dongyan Institute of Computer Science & Technology NLP&CC 2012 – Beijing, China

2 Outline Introduction Related Work Event definitions Existing event models News Ontology Event Model The Design of NOEM Main Concepts and Properties in NOEM Evaluation Conclusion -2- NLP&CC, Beijing, China

3 Introduction News Information Overload Numerous online news service providers Explosive increase of online news users Persons (Ten thousand ) Numbers of online news users and time they spend in browsing news -3- NLP&CC, Beijing, China

4 Introduction Classification & summarization are widely used in online news domain document-oriented techniques based on traditional BOW models can not provide sufficient event semantic information Users need intelligent event level semantic news services to push events but not documents to users employing entities and relations to provide semantic navigation, e.g., renlifang of Microsoft, soso waltz of Tencent renlifang of Microsoftsoso waltz of Tencent Web of DocumentWeb of Data Web of entity and relation -4- NLP&CC, Beijing, China

5 -5- Introduction How to provide multi-dimensional semantic navigation? 5W1H Who, When, Where, What, Why, How NLP&CC, Beijing, China

6 Introduction -6- Our research aim is semantic understanding of Chinese news by extracting entities, relations involved in a key event of a news story building a news events knowledge base as well as a semantic retrieval engine to support event level semantic applications We implemented a novel framework to address the whole list of 5W1H key event identification event semantic elements extraction Ontology-based event knowledge base construction This paper discusses Ontology-Based Event Modeling for Semantic Understanding of Chinese News Story NLP&CC, Beijing, China

7 5WIH elements extraction in key events of Chinese news story We try to build a practical Chinese event extraction system by combining Natural Language Processing technologies (Lexical analysis, NER) Machine Learning (SVM, CRF) Semantic Web technologies (Ontology, OWL, Rules) Chinese Online News Methodology Key event identification in one news story Event knowledge base Event semantic modeling and ontology population 5W1H event semantic-elements extraction -7- NLP&CC, Beijing, China

8 Outline Introduction Related Work Event Definitions Existing Event Models News Ontology Event Model The Design of NOEM Main Concepts and Properties in NOEM Evaluation Conclusion -8- NLP&CC, Beijing, China

9 Related Work Event Definitions WordNet something that happens at a given place and time. Cognitive psychologists happenings in the outside world, people observe and understand the world through event. Linguists (Chung and Timberlake, 1985) an event can be defined in terms of three components: a predicate; an interval of time on which the predicate occurs and a situation or set of conditions under which the predicate occurs. TimeML a cover term for situations that happen or occur. Events can be punctual or last for a period of time. ACE (Automatic Content Extraction) an event involving zero or more ACE entities, values and time expressions Event-based summarization atomic events: link major constituent parts (participants, locations, times) of events through verbs or action nouns labeling the event itself. -9- NLP&CC, Beijing, China

10 Related Work -10- NLP&CC, Beijing, China, where S, P, O are core elements and T, L are subordinates. We define event as an event is a specific occurrence which involves in some participants. It has three components: a predicate; core participants, i.e., agents and patients; auxiliary participants, i.e., time and location of the event. These participants are usually named entities which correspond to what, who, whom, when, where elements of an event.

11 Related Work -11- NLP&CC, Beijing, China Existing Event Models Script Theory, Event Domain Cognitive Model Cognitive linguistics Probabilistic Event Model TDT Atomic Event Model Event-based automatic summarization Structural Event Model MUC & ACE Generic Event Model Eventcentric multimedia data management Ontology Event Models ABC, PROTON, EO (Event Ontology), Event-Model-F

12 Outline Introduction Related Work Event Definitions Existing Event Models News Ontology Event Model The Design of NOEM Main Concepts and Properties in NOEM Evaluation Conclusion -12- NLP&CC, Beijing, China

13 News Ontology Event Model Modeling (1) event information, (2) event relations, (3) event media -13- NLP&CC, Beijing, China

14 Main concepts Relations News Ontology Event Model -14- NLP&CC, Beijing, China

15 Outline Introduction Related Work Event Definitions Existing Event Models News Ontology Event Model The Design of NOEM Main Concepts and Properties in NOEM Evaluation Conclusion -15- NLP&CC, Beijing, China

16 Evaluation -16- Janez Brank et. al. classified ontology evaluation methods into four categories: (1) Comparing the ontology to a golden standard; (2) Using an ontology in an application and evaluating the results; (3) Comparing with a source of data about the domain to be covered by the ontology; (4) Evaluation is done by humans who try to assess how well the ontology meets a set of predefined criteria, standards, requirements. NLP&CC, Beijing, China

17 Comparison between NOEM and existing event models Evaluation -17- NLP&CC, Beijing, China

18 Evaluation -18- Manual labeling 4 postgraduates Chinese News stories from Xinhua news agency Covers 23 top classes and 2082 subclasses of CNML In 85% of them, we found a topic sentence which contains key event of the news 4/5Ws in the topic sentence which can be described by NOEM appropriately Category codeCategory nameSubclasses NLP&CC, Beijing, China

19 Evaluation: A Case Study Chinese President Hu Jintao arrived in Canada for a state visit Result of 5W1H extraction of key event, …… 5W1H Extraction -19- NLP&CC, Beijing, China

20 Evaluation: Population of NOEM An automatic generated OWL File Chinese President Hu Jintao arrived in Canada for a state visit Ontology Population -20- NLP&CC, Beijing, China

21 Outline Introduction Related Work Event Definitions Existing Event Models News Ontology Event Model The Design of NOEM Main Concepts and Properties in NOEM Evaluation Conclusion -21- NLP&CC, Beijing, China

22 Conclusion -22- NLP&CC, Beijing, China Main contributions an extensive investigation of event and event modeling the usage of concept of 5W1H semantic elements in Chinese news domain the design of ontology-based event model: NOEM defining concepts of entities (time, person, location, organization etc.), events and relationships to capture temporal, spatial, information, experiential, structural and causal aspect, e.g. the 5W1H, of an event Future work building a news events knowledge base and a semantic retrieval engine on NOEM to support event level semantic applications

23 The End Thank you for your patience! Q&A

24 Framework A streamline of three steps and six sub-tasks (1) Title classification and (2) topic sentences extraction for key event identification; (3) Semantic role labeling and (4) 5W1H elements identification for event semantic elements extraction; (5) NOEM definition and (6) Ontology population for event knowledge base construction NLP&CC, Beijing, China

25 Publications Please see our previous work for more details Key Event Extraction Wang, W., Zhao, D., Zhao, W.: Identification of topic sentence about key event in Chinese News. Acta Scientiarum Naturalium Universitatis Pekinensis 47(5),789–796 (2011). 5Ws Extraction Wang, W., Zhao, D., Zou, L., Wang, D., Zheng, W.: Extracting 5W1H Event Semantic Elements from Chinese Online News. In: Chen, L., Tang, C., Yang, J., Gao, Y. (eds.) WAIM LNCS, vol. 6184, pp. 644–655. Springer, Heidelberg (2010) Wang W., Zhao D., Wang D.: Chinese news event 5w1h elements extraction using semantic role labeling. In: the 3th ISIP. pp. 484–489(2010) Framework Wang, W., Zhao, D.: Chinese News Event 5W1H Semantic Elements Extraction for Event Ontology Population. WWW2012 PhD symposium. Lyon, France. (2012) -25- NLP&CC, Beijing, China

26 -26- NLP&CC, Beijing, China

27 Title Based Key Event Extraction Input: News document Output: Topic sentences Begin NLP-based Preprocessing: Title classification; // classified the title into informative or non-informative Topic words extraction; // 1)TFIDF; 2) PageRank in word co-occurrence graph Title & Topic words co-occurrence analysis; //(1) For each sentence do: Term frequency scoring; //(2) Sentence location scoring; //(3) Sentence length scoring; //(4) Name entity scoring; //(5) Sentence and title similarity scoring; //(6) Sentence weighting & ranking; //(8) End do End -27- NLP&CC, Beijing, China

28 Chinese News Semantic Elements Extraction Input: Topic Sentences Output: & How of news Begin For each topic sentence do 1) NE recognition; 2) NP recognition; 3) Event identification and classification by verb-driven & SVM ; 4) Syntactic-semantic rules-based recognition; 5) Time expressions identification and normalization; 6) Location identification; 7) Topic sentences as short summarization; End do End Who did what to whom When Where How CRF-based NP tagger HMM-based NER tool What -28- NLP&CC, Beijing, China


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