34,282 research outputs found
Diversifying Search Results Using Time
Getting an overview of a historic entity or event can be difficult in search results, especially if important dates concerning the entity or event are not known beforehand. For such information needs, users would benefit if returned results covered diverse dates, thus giving an overview of what has happened throughout history. Diversifying search results based on important dates can be a building block for applications, for instance, in digital humanities. Historians would thus be able to quickly explore longitudinal document collections by querying for entities or events without knowing associated important dates apriori. In this work, we describe an approach to diversify search results using temporal expressions (e.g., in the 1990s) from their contents. Our approach first identifies time intervals of interest to the given keyword query based on pseudo-relevant documents. It then re-ranks query results so as to maximize the coverage of identified time intervals. We present a novel and objective evaluation for our proposed approach. We test the effectiveness of our methods on the New York Times Annotated corpus and the Living Knowledge corpus, collectively consisting of around 6 million documents. Using history-oriented queries and encyclopedic resources we show that our method indeed is able to present search results diversified along time
Intent Models for Contextualising and Diversifying Query Suggestions
The query suggestion or auto-completion mechanisms help users to type less
while interacting with a search engine. A basic approach that ranks suggestions
according to their frequency in the query logs is suboptimal. Firstly, many
candidate queries with the same prefix can be removed as redundant. Secondly,
the suggestions can also be personalised based on the user's context. These two
directions to improve the aforementioned mechanisms' quality can be in
opposition: while the latter aims to promote suggestions that address search
intents that a user is likely to have, the former aims to diversify the
suggestions to cover as many intents as possible. We introduce a
contextualisation framework that utilises a short-term context using the user's
behaviour within the current search session, such as the previous query, the
documents examined, and the candidate query suggestions that the user has
discarded. This short-term context is used to contextualise and diversify the
ranking of query suggestions, by modelling the user's information need as a
mixture of intent-specific user models. The evaluation is performed offline on
a set of approximately 1.0M test user sessions. Our results suggest that the
proposed approach significantly improves query suggestions compared to the
baseline approach.Comment: A short version of this paper was presented at CIKM 201
Explicit diversification of event aspects for temporal summarization
During major events, such as emergencies and disasters, a large volume of information is reported on newswire and social media platforms. Temporal summarization (TS) approaches are used to automatically produce concise overviews of such events by extracting text snippets from related articles over time. Current TS approaches rely on a combination of event relevance and textual novelty for snippet selection. However, for events that span multiple days, textual novelty is often a poor criterion for selecting snippets, since many snippets are textually unique but are semantically redundant or non-informative. In this article, we propose a framework for the diversification of snippets using explicit event aspects, building on recent works in search result diversification. In particular, we first propose two techniques to identify explicit aspects that a user might want to see covered in a summary for different types of event. We then extend a state-of-the-art explicit diversification framework to maximize the coverage of these aspects when selecting summary snippets for unseen events. Through experimentation over the TREC TS 2013, 2014, and 2015 datasets, we show that explicit diversification for temporal summarization significantly outperforms classical novelty-based diversification, as the use of explicit event aspects reduces the amount of redundant and off-topic snippets returned, while also increasing summary timeliness
Limited Liability and the Known Unknown
Limited liability is a double-edged sword. On the one hand, limited lia-bility may help overcome investors’ risk aversion and facilitate capital formation and economic growth. On the other hand, limited liability is widely believed to contribute to excessive risk-taking and externaliza-tion of losses to the public. The externalization problem can be mitigated imperfectly through existing mechanisms such as regulation, mandatory insurance, and minimum capital requirements. These mechanisms would be more effective if information asymmetries between industry and poli-cymakers were reduced. Private businesses typically have better infor-mation about industry-specific risks than policymakers.
A charge for limited liability entities—resembling a corporate income tax but calibrated to risk levels—could have two salutary effects. First, a well-calibrated limited liability tax could help compensate the public fisc for risks and reduce externalization. Second, a limited liability tax could force private industry actors to reveal information to policymakers and regulators, thereby dynamically improving the public response to externalization risk.
Charging firms for limited liability at initially similar rates will lead relatively low-risk firms to forgo limited liability, while relatively high-risk firms will pay for limited liability. Policymakers will then be able to focus on the industries whose firms have self-identified as high risk, and thus develop more finely tailored regulatory responses. Because the ben-efits of making the proper election are fully internalized by individual firms, whereas the costs of future regulation or limited liability tax changes will be borne collectively by industries, firms will be unlikely to strategically mislead policymakers in electing limited or unlimited lia-bility. By helping to reveal private information and focus regulators’ at-tention, a limited liability tax could accelerate the pace at which poli-cymakers learn, and therefore, the pace at which regulations improve
Interactive Search and Exploration in Online Discussion Forums Using Multimodal Embeddings
In this paper we present a novel interactive multimodal learning system,
which facilitates search and exploration in large networks of social multimedia
users. It allows the analyst to identify and select users of interest, and to
find similar users in an interactive learning setting. Our approach is based on
novel multimodal representations of users, words and concepts, which we
simultaneously learn by deploying a general-purpose neural embedding model. We
show these representations to be useful not only for categorizing users, but
also for automatically generating user and community profiles. Inspired by
traditional summarization approaches, we create the profiles by selecting
diverse and representative content from all available modalities, i.e. the
text, image and user modality. The usefulness of the approach is evaluated
using artificial actors, which simulate user behavior in a relevance feedback
scenario. Multiple experiments were conducted in order to evaluate the quality
of our multimodal representations, to compare different embedding strategies,
and to determine the importance of different modalities. We demonstrate the
capabilities of the proposed approach on two different multimedia collections
originating from the violent online extremism forum Stormfront and the
microblogging platform Twitter, which are particularly interesting due to the
high semantic level of the discussions they feature
Leachate treatment by conventional coagulation, electrocoagulation and two-stage coagulation (conventional coagulation and electrocoagulation)
Leachate is widely explored and investigated due to highly polluted and difficult to treat. Leachate treatment commonly involves advanced, complicated and high cost activities. Conventional coagulation is widely used in the treatment of wastewater but the sludge production becomes the biggest constraint in this treatment. Electrocoagulation is an alternative to conventional method because it has the same application but produce less sludge and requires simple equipment. Thus, combination of conventional coagulation and electrocoagulation can improve the efficiency of coagulation process in leachate treatment. This article is focusing on the efficiency of single and combined treatment as well as the improvement made by combined treatment. Based on review, the percentage reduction of current density and dose of coagulant was perceptible. As much 50% reduction of current density, duration of treatment, and dose of coagulant able to be obtained by using combined treatment. This combined treatment is able to reduce the cost and at the same time reduce the duration of treatment. Hence, the combined treatment offers an alternative technique for landfill leachate treatment on the removal of pollutants
Am I the Only Person Paying Taxes? The Largest Tax Loophole for the Rich - Exchange Funds
President Obama is faced with a national debt at over 30 billion Exchange Funds.
This Article addresses the social equity arguments and the tax and economic theories to solve the perceived problem. The Article thoroughly covers, through unique access to materials not available in traditional legal sources, including fund private placement memorandum, the basics of fund details, fund formations, and the tax rules, and suggests solutions to solve the social inequity.
This Article not only proposes how to create legislation to tax the current arrangements but offers a solution utilizing the Code and Regulations to tax these vehicles
Searching for managerial opportunism faint traces in French diversifying acquisitions
We are looking for traces of managerial opportunism in french diversifyingacquisitions. Indeed, following various theories, diversification is seeking by managers.Furthermore, recent empiric evidences show that corporate diversification is valuedestructive for shareholders. Using classical OLS methodology with diversification,management ownership and performance variables, we find some evidence of managerialopportunism. But classical methodology presents two shortages. First, it supposed a uniquesense of causality. In particular, firm diversification is supposed to impact firmperformance without considering the inverse relationship (from performance todiversification). This one-way analysis can create biases in the estimated results. Second,this OLS methodology doesn't permit to take simultaneously the relationship between ourvariables. Noticing that this classical methodology is not well adapted to the problem, wesubmit our data to a system of simultaneous equations. Using this system, according to usbetter adapted, the faint traces of managerial opportunism vanishes. This is the case inparticular because the negative impact of diversification on performance disappears whenwe consider a non recursive relation between the variables. We derive others surprisingresults from our simultaneaous equations framework. Management stake in the equity caninfluence or be influenced by the performance depending on wether the performance ismeasured at the firm or at the operation (acquisition) level. Together, these results suggestthat we have to be cautious when searching for managerial opportunism in sample andstatistical studies. If manager opportunist inclination can be suspected in this kind ofstudies, it has to be distinguished from manager opportunist behavior which is far moredifficult to exhibit.managerial opportunism;acquisition;corporate diversification;agence;performance
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