Using Markov Chains for link prediction in adaptive web sites

The large number of Web pages on many Web sites has raised navigational problems. Markov chains have recently been used to model user navigational behavior on the World Wide Web (WWW). In this paper, we propose a method for constructing a Markov model of a Web site based on past visitor behavior. We use the Markov model to make link predictions that assist new users to navigate the Web site. An algorithm for transition probability matrix compression has been used to cluster Web pages with similar transition behaviors and compress the transition matrix to an optimal size for efficient probability calculation in link prediction. A maximal forward path method is used to further improve the efficiency of link prediction. Link prediction has been implemented in an online system called ONE (Online Navigation Explorer) to assist users' navigation in the adaptive Web site

The Impact of Link Suggestions on User Navigation and User Perception

The study reported in this paper explores the effects of providing web users with link suggestions that are relevant to their tasks. Results indicate that link suggestions were positively received. Furthermore, users perceived sites with link suggestions as more usable and themselves as less disoriented. The average task execution time was significantly lower than in the control condition and users appeared to navigate in a more structured manner. Unexpectedly, men took more advantage from link suggestions than women

Accelerating Agriculture Productivity Improvement in Bangladesh: Mitigation co-benefits of nutrients and water use efficency

Analysis of potential mitigation in the development project Accelerating Agriculture Productivity Improvement (AAPI) in Bangladesh showed a 2% reduction in greenhouse gas (GHG) emissions, driven by urea deep placement (UDP) and alternate wetting and drying (AWD) in flooded rice systems. Given high emissions associated with conventional irrigated rice production, this represents a substantial reduction in emissions. AAPI promotes UDP, a fertilization practice known to increase nitrogen uptake efficiency. Based on the project plan and progress of implementation, UDP adoption was anticipated on 1.1 million ha of aman rice and 700,000 ha of boro rice. UDP is an example of the absolute emission reductions that are possible when a practice is widely implemented. AAPI promotes AWD, an irrigation practice for rice that reduces the amount of water used and results in decreased emissions. AAPI tested AWD on a pilot scale (21,000 ha). Climate change mitigation benefits would increase dramatically if adoption of AWD were more widespread. Due to increased rice yields, UDP and AWD reduce the emission intensity (CO2e emitted per kg production) from rice production by 10–48%

Better Life Alliance in Zambia: Climate change mitigation as a co-benefit of improved landscape, agroforestry, soil, and fertilizer management

Analysis of agricultural activities in the Better Life Alliance (BLA) project in Zambia showed potential reduction in greenhouse gas emissions (GHG), mostly (85%) due to avoided savanna degradation and conversion. The GHG impact due to BLA’s interventions is estimated at –902,531 tCO2e/yr, equivalent to saving 2,089,550 barrels of oil. BLA’s business model linked prevention of degradation and conversion of shrubland to market-based incentives for agricultural crops, thereby providing farmers with economic incentives for conservation and climate change mitigation. BLA promoted a comprehensive approach to soil fertility management. It promoted agroecological approaches such as recycling farm organic resources, planting nitrogen-fixing trees, minimal tillage, and cover crops. BLA reduced postharvest loss (PHL) through improved product processing, storage, and packaging. Changes in PHL were estimated for groundnuts (–100%), maize (–40%), rice (–80%), and soybeans (–67%), which contributed to decreases in emission intensity (GHG emissions per unit of production) for each of these products

Peru Cacao Alliance: Carbon sequestration as a co-benefit of cacao expansion

The agricultural development project, Peru Cacao Alliance (PCA), has contributed to climate change mitigation. Estimated carbon sequestration from perennial crop expansion, which was –211,467 tCO2e metric tonnes of carbon dioxide equivalent per year, more than offset increased greenhouse gas emission (GHG) from fertilizer and pesticide management (10,286 tCO2e). The net difference, –201,180 tCO2e, is equivalent to the carbon content of 465,774 barrels of oil. The agroforestry system promoted by PCA included cacao and shade trees. Since PCA could not provide definitive data detailing the presence of existing shade trees compared to the planting of new shade trees, this analysis did not include carbon dynamics of shade trees. If new trees were planted for shade, there would be greater carbon uptake by the system than presented in this analysis. PCA reduced emissions intensity for cacao (CO2e emitted per kg production) through improved carbon sequestration and increased yields. PCA improved cacao postharvest handling (proper pod selection, storage, drying and fermentation methods) by building knowledge and capacity in producer organizations

An analysis of the cost and benefit of search interactions

Interactive Information Retrieval (IR) systems often provide various features and functions, such as query suggestions and relevance feedback, that a user may or may not decide to use. The decision to take such an option has associated costs and may lead to some benefit. Thus, a savvy user would take decisions that maximises their net benefit. In this paper, we formally model the costs and benefits of various decisions that users, implicitly or explicitly, make when searching. We consider and analyse the following scenarios: (i) how long a user's query should be? (ii) should the user pose a specific or vague query? (iii) should the user take a suggestion or re-formulate? (iv) when should a user employ relevance feedback? and (v) when would the "find similar" functionality be worthwhile to the user? To this end, we build a series of cost-benefit models exploring a variety of parameters that affect the decisions at play. Through the analyses, we are able to draw a number of insights into different decisions, provide explanations for observed behaviours and generate numerous testable hypotheses. This work not only serves as a basis for future empirical work, but also as a template for developing other cost-benefit models involving human-computer interaction

ACCESO in Honduras: Mitigation co-benefits of perennial crop expansion, soil management, and livestock improvements

The agricultural development project ACCESO reduced greenhouse gas emissions (GHG) and led to net carbon sequestration due to perennial crop expansion. Increased fertilizer use was a moderate source of emissions that was more than offset by reduced emissions from other ACCESOsupported practices, including improvements in soil, water, and fertilizer management, and in feed and grassland use by dairy cows. Compared to conventional practices, ACCESOsupported activities reduced emission intensity (GHG emissions per kilogram of output) for carrots (-106%), cabbages (-99%), maize (-99%), and potatoes (-98%) compared to conventional production methods. Emission intensity increased due to greater fertilizer use for plantain (55%) and coffee (247%)

Pastoralist Areas Resilience Improvement through Market Expansion (PRIME) in Ethiopia: Mitigation co-benefits of livestock productivity

Pastoralist Areas Resilience Improvement through Market Expansion (PRIME) showed a notable decrease in emission intensity (GHG emissions per unit of meat or milk). PRIME enabled farmers to increase production significantly, between 24% and 96%, which led to a decrease in emission intensity ranging from -4% to -42%. Due to improvements in feed quantity, PRIME projected an increase in average animal weight for all livestock (8.3 million head), which resulted in an increase in GHG emissions by an estimated 1.5 million tCO2e/yr. PRIME empowered stakeholders collectively to design and establish plans for effective management of pastures and water. The project supported soil and water conservation measures, enclosing degraded pastures, selective bush thinning, and clearing the invasive plant Prosopis. These practices improved pasture plant quality and reduced bare soil and overgrazing, which resulted in increased sequestration of soil carbon. These grassland improvements were estimated to sequester -0.1 million tCO2e/yr

Reducing food loss in agricultural development projects through value chain efficiency

Food loss and waste (FLW) reduces the amount of food available for distribution and consumption, decreases food security, and increases the environmental burden of food production. Combating FLW addresses the key pillars of climate-smart agriculture for farmers by increasing productivity, promoting adaption to climate change, and mitigating greenhouse gas emissions. Although studies of interventions to reduce FLW exist, almost no research systematically investigates FLW interventions across value chains or in multiple countries, most likely due to challenges in collecting and synthesizing multi-country estimates. Our research team investigated changes in FLW in projects supported by the United States Government’s global hunger and food security initiative: Feed the Future. This provided a unique opportunity to conduct ex-ante estimates of the impacts of interventions across 20 value chains in 12 countries based on interviews with United States Agency for International Development (USAID) and project staff. We provide specific examples of interventions used in each value chain and country context. The results provide an evidence base of interventions that successfully decreased FLW at multiple points along the food value chain, from upstream producer-dominated stages to downstream consumer-dominated stages. Results also show that no single FLW solution or intervention works across agriculture sub-sectors, value chain stages, and countries. Amongst the sub-sectors studied, results showed that FLW interventions directed at extensive dairy systems could provide meaningful greenhouse mitigation. In the dairy supply chain, FLW estimates ranged from 5-50% in the business-as- usual approach and declined 4-10% as a result of intervention

Evaluating implicit feedback models using searcher simulations

In this article we describe an evaluation of relevance feedback (RF) algorithms using searcher simulations. Since these algorithms select additional terms for query modification based on inferences made from searcher interaction, not on relevance information searchers explicitly provide (as in traditional RF), we refer to them as implicit feedback models. We introduce six different models that base their decisions on the interactions of searchers and use different approaches to rank query modification terms. The aim of this article is to determine which of these models should be used to assist searchers in the systems we develop. To evaluate these models we used searcher simulations that afforded us more control over the experimental conditions than experiments with human subjects and allowed complex interaction to be modeled without the need for costly human experimentation. The simulation-based evaluation methodology measures how well the models learn the distribution of terms across relevant documents (i.e., learn what information is relevant) and how well they improve search effectiveness (i.e., create effective search queries). Our findings show that an implicit feedback model based on Jeffrey's rule of conditioning outperformed other models under investigation