Abstract
Due to the increasing availability of huge amounts of data, traditional data management techniques result inadequate in many real life scenarios. Furthermore, heterogeneity and high speed of this data require suitable data storage and management tools to be designed from scratch. In this paper, we describe a framework tailored for analyzing user interactions with intelligent systems while seeking for some domain specific information (e.g., choosing a good restaurant in a visited area). The framework enhances user quest for information by performing a data exchange activity (called data posting) which enriches the information sources with additional background information and knowledge derived from experiences and behavioral properties of domain experts and users.
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- 1.
As a matter of fact, due to its quick result presentation, many users go through Google even if they exactly know the URLs of the resources they are interested in.
- 2.
For the sake of generalization we do not distinguish between query text and post as both of them can be considered as plain text objects.
- 3.
In this paper we refer to the hard clustering problem, where every data point belongs to exactly one cluster.
- 4.
Also in OLAP analysis, attributes used to highlight properties of raw data (mainly, by categorization and grouping) are called dimensions – we recall that an OLAP system is characterized by multidimensional data cubes that enable manipulation and analysis of data stored in a source database from multiple perspectives (see for instance [5]).
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Cassavia, N., Masciari, E., Pulice, C., Saccà, D. (2016). A Framework Enhancing the User Search Activity Through Data Posting. In: Alferes, J., Bertossi, L., Governatori, G., Fodor, P., Roman, D. (eds) Rule Technologies. Research, Tools, and Applications. RuleML 2016. Lecture Notes in Computer Science(), vol 9718. Springer, Cham. https://doi.org/10.1007/978-3-319-42019-6_19
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