Finding Relevant Answers in Software Forums

Abstract—Online software forums provide a huge amount of valuable content. Developers and users often ask questions and receive answers from such forums. The availability of a vast amount of thread discussions in forums provides ample opportunities for knowledge acquisition and summarization. For a given search query, current search engines use traditional information retrieval approach to extract webpages containin

The ecology of seamounts: structure, function, and human impacts.

In this review of seamount ecology, we address a number of key scientific issues concerning the structure and function of benthic communities, human impacts, and seamount management and conservation. We consider whether community composition and diversity differ between seamounts and continental slopes, how important dispersal capabilities are in seamount connectivity, what environmental factors drive species composition and diversity, whether seamounts are centers of enhanced biological productivity, and whether they have unique trophic architecture. We discuss how vulnerable seamount communities are to fishing and mining, and how we can balance exploitation of resources and conservation of habitat. Despite considerable advances in recent years, there remain many questions about seamount ecosystems that need closer integration of molecular, oceanographic, and ecological research

Dating the Cryptococcus gattii Dispersal to the North American Pacific Northwest.

The emergence of Cryptococcus gattii, previously regarded as a predominantly tropical pathogen, in the temperate climate of the North American Pacific Northwest (PNW) in 1999 prompted several questions. The most prevalent among these was the timing of the introduction of this pathogen to this novel environment. Here, we infer tip-dated timing estimates for the three clonal C. gattii populations observed in the PNW, VGIIa, VGIIb, and VGIIc, based on whole-genome sequencing of 134 C. gattii isolates and using Bayesian evolutionary analysis by sampling trees (BEAST). We estimated the nucleotide substitution rate for each lineage (1.59 × 10-8, 1.59 × 10-8, and 2.70 × 10-8, respectively) to be an order of magnitude higher than common neutral fungal mutation rates (2.0 × 10-9), indicating a microevolutionary rate (e.g., successive clonal generations in a laboratory) in comparison to a species' slower, macroevolutionary rate (e.g., when using fossil records). The clonal nature of the PNW C. gattii emergence over a narrow number of years would therefore possibly explain our higher mutation rates. Our results suggest that the mean time to most recent common ancestor for all three sublineages occurred within the last 60 to 100 years. While the cause of C. gattii dispersal to the PNW is still unclear, our research estimates that the arrival is neither ancient nor very recent (i.e., <25 years ago), making a strong case for an anthropogenic introduction. IMPORTANCE The recent emergence of the pathogenic fungus Cryptococcus gattii in the Pacific Northwest (PNW) resulted in numerous investigations into the epidemiological and enzootic impacts, as well as multiple genomic explorations of the three primary molecular subtypes of the fungus that were discovered. These studies lead to the general conclusion that the subtypes identified likely emerged out of Brazil. Here, we conducted genomic dating analyses to determine the ages of the various lineages seen in the PNW and propose hypothetical causes for the dispersal events. Bayesian evolutionary analysis strongly suggests that these independent fungal populations in the PNW are all 60 to 100 years old, providing a timing that is subsequent to the opening of the Panama Canal, which allowed for more direct shipping between Brazil and the western North American coastline, a possible driving event for these fungal translocation events

Causal Collaborative Filtering

Recommender systems are important and valuable tools for many personalized services. Collaborative Filtering (CF) algorithms -- among others -- are fundamental algorithms driving the underlying mechanism of personalized recommendation. Many of the traditional CF algorithms are designed based on the fundamental idea of mining or learning correlative patterns from data for matching, including memory-based methods such as user/item-based CF as well as learning-based methods such as matrix factorization and deep learning models. However, advancing from correlative learning to causal learning is an important problem, because causal/counterfactual modeling can help us to think outside of the observational data for user modeling and personalization. In this paper, we propose Causal Collaborative Filtering (CCF) -- a general framework for modeling causality in collaborative filtering and recommendation. We first provide a unified causal view of CF and mathematically show that many of the traditional CF algorithms are actually special cases of CCF under simplified causal graphs. We then propose a conditional intervention approach for $do$-calculus so that we can estimate the causal relations based on observational data. Finally, we further propose a general counterfactual constrained learning framework for estimating the user-item preferences. Experiments are conducted on two types of real-world datasets -- traditional and randomized trial data -- and results show that our framework can improve the recommendation performance of many CF algorithms.Comment: 14 pages, 5 figures, 3 table