Search (5 results, page 1 of 1)

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Abstract

Users increasingly acquire, share, and create knowledge in online knowledge communities, making them massive dynamic knowledge repositories that spark inspiration. While online knowledge communities provide powerful searching tools, they ignore the potential of serendipity in fostering knowledge acquisition. Against this backdrop, this research investigates whether serendipity can be stimulated by design features of communities. Specifically, we examine whether different tag presentation formats may promote serendipity. Two hundred seven participants were randomly assigned to our experimental website that displays one of three tag formats. Results show that users experienced serendipity more frequently while using tag trees than tag clouds, followed by tag lists. Moreover, tag formats moderate how openness to experience affects serendipity. Although openness did not influence serendipity across tag formats, further analysis shows that it significantly decreases serendipity for tag lists, but significantly increases serendipity for tag clouds and trees. Theoretically, these results provide an in-depth understanding of serendipity that is contingent on the interaction between community design features and personality (e.g., openness to experience). Practically, these findings demonstrate how interface features (e.g., tag presentation formats) facilitate serendipity, thus informing better design of online knowledge communities to improve the efficiency of knowledge acquisition.

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Abstract

Role analysis plays an important role when exploring social media and knowledge-sharing platforms for designing marking strategies. However, current methods in role analysis have overlooked content generated by users (e.g., posts) in social media and hence focus more on user behavior analysis. The user-generated content is very important for characterizing users. In this paper, we propose a novel method which integrates both user behavior and posted content by users to identify roles in online social networks. The proposed method models a role as a joint distribution of Gaussian distribution and multinomial distribution, which represent user behavioral feature and content feature respectively. The proposed method can be used to determine the number of roles concerned automatically. The experimental results show that the proposed method can be used to identify various roles more effectively and to get more insights on such characteristics.

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Abstract

With the advent of various services and applications of Semantic Web, semantic annotation has emerged as an important research topic. The application of semantically annotated ontology had been evident in numerous information processing and retrieval tasks. One of such tasks is utilizing the semantically annotated ontology in product design which is able to suggest many important applications that are critical to aid various design related tasks. However, ontology development in design engineering remains a time consuming and tedious task that demands considerable human efforts. In the context of product family design, management of different product information that features efficient indexing, update, navigation, search and retrieval across product families is both desirable and challenging. For instance, an efficient way of retrieving timely information on product family can be useful for tasks such as product family redesign and new product variant derivation when requirements change. However, the current research and application of information search and navigation in product family is mostly limited to its structural aspect which is insufficient to handle advanced information search especially when the query targets at multiple aspects of a product. This paper attempts to address this problem by proposing an information search and retrieval framework based on the semantically annotated multi-facet product family ontology. Particularly, we propose a document profile (DP) model to suggest semantic tags for annotation purpose. Using a case study of digital camera families, we illustrate how the faceted search and retrieval of product information can be accomplished. We also exemplify how we can derive new product variants based on the designer's query of requirements via the faceted search and retrieval of product family information. Lastly, in order to highlight the value of our current work, we briefly discuss some further research and applications in design decision support, e.g. commonality analysis and variety comparison, based on the semantically annotated multi-facet product family ontology.

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Date

22. 6.1997 16:34:51

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Date

20. 1.2015 18:30:22