As the popularity of content sharing websites has increased, they have become targets for spam, phishing and the distribution of malware. On YouTube, the facility for users to post comments can be used by spam campaigns to direct unsuspecting users to malicious third-party websites. In this paper, we demonstrate how such campaigns can be tracked over time using network motif profiling, i.e. by tracking counts of indicative network motifs. By considering all motifs of up to five nodes, we identify discriminating motifs that reveal two distinctly different spam campaign strategies, and present an evaluation that tracks two corresponding active campaigns.
This paper describes a general framework for learning Higher-Order Network Embeddings (HONE) from graph data based on network motifs. The HONE framework is highly expressive and flexible with many interchangeable components. The experimental results demonstrate the effectiveness of learning higher-order network representations. In all cases, HONE outperforms recent embedding methods that are unable to capture higher-order structures with a mean relative gain in AUC of $19\%$ (and up to $75\%$ gain) across a wide variety of networks and embedding methods.
This paper addresses the problem of activity and event discovery in multi dimensional time series data by proposing a novel method for locating multi dimensional motifs in time series. While recent work has been done in finding single dimensional and multi dimensional motifs in time series, we address motifs in general case, where the elements of multi dimensional motifs have temporal, length, and frequency variations. The proposed method is validated by synthetic data, and empirical evaluation has been done on several wearable systems that are used by real subjects.
Fluorine plays a supporting role in some of the best-known hypervalent compounds, such as PF5 and SF6. Goesten et al. now suggest that the halogen can also play the lead part in constrained environs. Using density functional theory, the authors report that all eight engage in stabilizing Si-F orbital interactions. Whereas hypervalency is more often associated with third- and fourth-row elements, in this motif, sterics preclude analogous bonding to the heavier halides.
In this spirit, Sali and Blundell (1990) develop an elaborate scheme for the comparison of protein structures. The results of a comparison form a "generalized protein," which can be used in predicting 3D conformation of the sequence of the unknown. Similar to the work of Lathrop et al. (1987), proteins are described by a hierarchy, with each level being a sequence of typed elements. Elements of fragments are represented by a host of computed properties, rather than by a single identifier. Attributes of fragment elements can refer to other elements in the sequence, thus representing binary relationships such as hydrogen bonding between elements.