TimeMachine: Timeline Generation for Knowledge-Base Entities

We present a method called TIMEMACHINE to generate a timeline of events and relations for entities in a knowledge base. For example for an actor, such a timeline should show the most important professional and personal milestones and relationships such as works, awards, collaborations, and family relationships. We develop three orthogonal timeline quality criteria that an ideal timeline should satisfy: (1) it shows events that are relevant to the entity; (2) it shows events that are temporally diverse, so they distribute along the time axis, avoiding visual crowding and allowing for easy user interaction, such as zooming in and out; and (3) it shows events that are content diverse, so they contain many different types of events (e.g., for an actor, it should show movies and marriages and awards, not just movies). We present an algorithm to generate such timelines for a given time period and screen size, based on submodular optimization and web-co-occurrence statistics with provable performance guarantees. A series of user studies using Mechanical Turk shows that all three quality criteria are crucial to produce quality timelines and that our algorithm significantly outperforms various baseline and state-of-the-art methods.Comment: To appear at ACM SIGKDD KDD'15. 12pp, 7 fig. With appendix. Demo and other info available at http://cs.stanford.edu/~althoff/timemachine

Temporal stability of soil moisture spatial variability at two scales and its implication for optimal field monitoring

International audienceSoil moisture spatial distribution is a key component in characterizing and modeling water movement at multiple scales. The temporal stability of soil moisture spatial distribution at multiple depths was investigated at the 7.9-ha Shale Hills Catchment in central Pennsylvania with a year-round monitoring of 77 sites distributed across the catchment. For this catchment with heterogeneous soils and landforms, integration of soils information into the temporal stability assessment provided a more accurate location of representative monitoring sites for capturing mean soil moisture. The temporal stability pattern of soil moisture at the swale scale was similar to that at the catchment scale, suggesting that the swale could be used as a representative unit in the catchment study in terms of mean soil moisture dynamics. The temporal stability of soil moisture variability in this catchment varied over space and seasons. Temporally stable sites were found in the northwestern and southeastern parts of the catchment, while the areas near the stream and some swale areas had lower temporal stability. The spatial distribution of soil moisture was more stable over time during wet seasons, but less stable during transitional periods (i.e. drying or recharging periods). The temporal stability concept helps the optimal design of field monitoring sites and sampling strategies. On the other hand, the temporally unstable sites provide insights regarding the hydrological processes behind the spatial variability of soil moisture

Wilson ratio of Fermi gases in one dimension

We calculate the Wilson ratio of the one-dimensional Fermi gas with spin imbalance. The Wilson ratio of attractively interacting fermions is solely determined by the density stiffness and sound velocity of pairs and of excess fermions for the two-component Tomonaga-Luttinger liquid (TLL) phase. The ratio exhibits anomalous enhancement at the two critical points due to the sudden change in the density of states. Despite a breakdown of the quasiparticle description in one dimension, two important features of the Fermi liquid are retained, namely the specific heat is linearly proportional to temperature whereas the susceptibility is independent of temperature. In contrast to the phenomenological TLL parameter, the Wilson ratio provides a powerful parameter for testing universal quantum liquids of interacting fermions in one, two and three dimensions.Comment: 5+2 pages, 4+1 figures, Eq. (4) is proved, figures were refine