Sandeep Mane

Dominance rank influences female space use in wild chimpanzees, Pan troglodytes: towards an ideal despotic distribution

Studies from many different taxa have demonstrated that dominance rank greatly influences individual space use. While the importance of dominance among female chimpanzees, Pan troglodytes, was debated in the past, mounting evidence now shows that rank is very important. In particular, rank has been shown to influence body mass, foraging strategies, association patterns, and ultimately, reproductive success. In this study, we investigated how rank influenced female space use among chimpanzees, P.t. schweinfurthii, at Gombe National Park, Tanzania. Analysing 10 years of data, we found that new immigrants used areas away from dominant females, and that subordinates had lower site fidelity. We also found that high-ranking females had smaller core areas and that this size difference was pronounced during periods of food scarcity when food competition is highest. These patterns suggest that dominant females outcompete subordinates, forcing them to settle elsewhere, range more widely, and shift their space use across time.

Adult Male Chimpanzees Inherit Maternal Ranging Patterns

Space use often correlates with reproductive success [1, 2]. Individual site fidelity is ubiquitous across a variety of taxa, including birds, mammals, insects, and reptiles [3-9]. Individuals can benefit from using the same area because doing so affords access to known resources, including food and/or breeding sites. The majority of studies on site fidelity have focused upon strictly territorial species in which individuals range in well-defined, exclusive areas (e.g., [4, 9]). By comparison, the transient groups that define fission-fusion species allow for considerable flexibility in individual space use. Although there is evidence that individual space use can influence reproductive success [2], relatively little is known about individual ranging patterns in fission-fusion species. Here, we investigate three potential correlates of male site fidelity (age, habitat quality, and maternal space use) in wild chimpanzees (Pan troglodytes). We found that when alone, each male preferentially concentrated his space use near the area where his mother ranged when he was dependent. We suggest that solitary ranging allows males to avoid direct competition with conspecifics and that foraging in familiar areas maximizes foraging efficiency. These results highlight the importance of male foraging strategies in a species in which male ranging is typically explained in terms of mating access to females.

Mining temporal patterns in popularity of web items

Huge amounts of various web items (e.g., images, keywords, and web pages) are being made available on the Web. The popularity of such web items continuously changes over time, and mining for temporal patterns in the popularity of web items is an important problem that is useful for several Web applications; for example, the temporal patterns in the popularity of web search keywords help web search enterprises predict future popular keywords, thus enabling them to make price decisions when marketing search keywords to advertisers. However, the presence of millions of web items makes it difficult to scale up previous techniques for this problem. This paper proposes an efficient method for mining temporal patterns in the popularity of web items. We treat the popularity of web items as time-series and propose a novel measure, a gap measure, to quantify the dissimilarity between the popularity of two web items. To reduce the computational overhead for this measure, an efficient method using the Discrete Fourier Transform (DFT) is presented. We assume that the popularity of web items is not necessarily periodic. For finding clusters of web items with similar popularity trends, we show the limitations of traditional clustering approaches and propose a scalable, efficient, density-based clustering algorithm using the gap measure. Our experiments using the popularity trends of web search keywords obtained from the Google Trends web site illustrate the scalability and usefulness of the proposed approach in real-world applications.

Concept-Aware Ranking: Teaching an Old Graph New Moves

In ranking algorithms for Web graphs, such as PageRank and HITS, the lack of attention to concepts/topics representing Web page content causes problems such as topic drift and mutually reinforcing relationships between hosts. This paper proposes a novel approach to expand the Web graph to incorporate conceptual information encoded by links (anchor text) between Web pages. Using Web graph link structure and conceptual information associated with each Web page (automatically extracted from anchor text of Minks), a new graph is defined where each node represents a unique pair of a Web page and concept associated with that Web page, and an edge represents an explicit or implicit link between two such nodes. This graph captures inter-concept relationships, which is then utilized by ranking algorithms. Our experimental results show that such an approach improves accuracy (e.g., first X precision) by retrieving links which are more authoritative given a users context