Sampled Weighted Min-Hashing for Large-Scale Topic Mining

We present Sampled Weighted Min-Hashing (SWMH), a randomized approach to automatically mine topics from large-scale corpora. SWMH generates multiple random partitions of the corpus vocabulary based on term co-occurrence and agglomerates highly overlapping inter-partition cells to produce the mined topics. While other approaches define a topic as a probabilistic distribution over a vocabulary, SWMH topics are ordered subsets of such vocabulary. Interestingly, the topics mined by SWMH underlie themes from the corpus at different levels of granularity. We extensively evaluate the meaningfulness of the mined topics both qualitatively and quantitatively on the NIPS (1.7 K documents), 20 Newsgroups (20 K), Reuters (800 K) and Wikipedia (4 M) corpora. Additionally, we compare the quality of SWMH with Online LDA topics for document representation in classification.Comment: 10 pages, Proceedings of the Mexican Conference on Pattern Recognition 201

Physical properties of CeGe2-x (x = 0.24) single crystals

We present data on the anisotropic magnetic properties, heat capacity and transport properties of CeGe2-x (x = 0.24) single crystals. The electronic coefficient of the heat capacity, gamma ~ 110 mJ/mol K^2, is enhanced; three magnetic transitions, with critical temperatures of ~ 7 K, ~ 5 K, and ~ 4 K are observed in thermodynamic and transport measurements. The ground state has a small ferromagnetic component along the c - axis. Small applied field, below 10 kOe, is enough to bring the material to an apparent saturated paramagnetic state (with no further metamagnetic transitions up to 55 kOe) with a reduced, below 1 mu_B, saturated moment