We consider the problem of predicting winners in elections, for the case where we are given complete knowledge about all possible candidates, all possible voters (together with their preferences), but where it is uncertain either which candidates exactly register for the election or which voters cast their votes. Under reasonable assumptions, our problems reduce to counting variants of election control problems. We either give polynomial-time algorithms or prove #P-completeness results for counting variants of control by adding deleting candidates voters for Plurality, k-Approval, Approval, Condorcet, and Maximin voting rules. We consider both the general case, where voters' preferences are unrestricted, and the case where voters' preferences are single-peaked.
From a technical standpoint, our research continues the line of work on the complexity of control. This line of work was initiated by Bartholdi, Tovey, and Trick @cite_20 , and then continued by Hemaspaandra, Hemaspaandra, and Rothe (who introduced the destructive cases), by (who considered multiwinner rules and who generalized the idea of the constructive and destructive cases), by Faliszewski, Hemaspaandra, and Hemaspaandra (who introduced multimode model of control), by Faliszewski, Hemaspaandra, and Hemaspaandra @cite_17 (who were first to consider control for weighted elections), by Rothe and Schend @cite_32 (who initiated the empirical study of the complexity of control problems), and by many other researchers, who provided results for specific voting rules and who introduced various other novel means of studying control problems (see, e.g., the following papers @cite_36 @cite_14 @cite_33 @cite_49 @cite_24 @cite_38 @cite_45 ; we also point the readers to the survey @cite_29 ).
@cite_38 @cite_14 @cite_33 @cite_36 @cite_29 @cite_32 @cite_24 @cite_45 @cite_49 @cite_20 @cite_17
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Control of elections refers to attempts by an agent to, via such actions as addition deletion partition of candidates or voters, ensure that a given candidate wins (Bartholdi, Tovey, & Trick 1992). An election system in which such an agent's computational task is NP-hard is said to be resistant to the given type of control. Aside from election systems with an NP-hard winner problem, the only systems known to be resistant to all the standard control types are highly artificial election systems created by hybridization (Hemaspaandra, Hemaspaandra, & Rothe 2007b). In this paper, we prove that an election system developed by the 13th century mystic Ramon Llull and the well-studied Copeland election system are both resistant to all the standard types of (constructive) electoral control other than one variant of addition of candidates. This is the most comprehensive resistance to control yet achieved by any natural election system whose winner problem is in P. In addition, we show that Llull and Copeland voting are very broadly resistant to bribery attacks, and we integrate the potential irrationality of voter preferences into many of our results. Manipulation, bribery, and control are well-studied ways of changing the outcome of an election. Many voting systems are, in the general case, computationally resistant to some of these manipulative actions. However when restricted to single-peaked electorates, these systems suddenly become easy to manipulate. Recently, Faliszewski, Hemaspaandra, and Hemaspaandra (2011b) studied the complexity of dishonest behavior in nearly single-peaked electorates. These are electorates that are not single-peaked but close to it according to some distance measure. In this paper we introduce several new distance measures regarding single-peakedness. We prove that determining whether a given profile is nearly single-peaked is NP-complete in many cases. For one case we present a polynomial-time algorithm. Furthermore, we explore the relations between several notions of nearly single-peakedness. A citing sentence is one that appears in a scientific article and cites previous work. Citing sentences have been studied and used in many applications. For example, they have been used in scientific paper summarization, automatic survey generation, paraphrase identification, and citation function classification. Citing sentences that cite multiple papers are common in scientific writing. This observation should be taken into consideration when using citing sentences in applications. For instance, when a citing sentence is used in a summary of a scientific paper, only the fragments of the sentence that are relevant to the summarized paper should be included in the summary. In this paper, we present and compare three different approaches for identifying the fragments of a citing sentence that are related to a given target reference. Our methods are: word classification, sequence labeling, and segment classification. Our experiments show that segment classification achieves the best results. Abstract Documents in computer-readable form can be used to provide information about other documents, i.e. those they cite. To do this efficiently requires procedures for computer recognition of citing statements. This is not easy, especially for multi-sentence citing statements. Computer recognition procedures have been developed which are accurate to the following extent: 73 of the words in statements selected by computer procedures as being citing statements are words which are correctly attributable to the corresponding documents. The retrieval effectiveness of computer-recognized citing statements was tested in the following way. First, for eight retrieval requests in inorganiic chemistry, average recall by search of Chemical Abstracts Service indexing and Chemical Abstracts abstract text words was found to be 50 . Words from citing statements referring to the papers to be retrieved were then added to the index terms and abstract words as additional access points, and searching was repeated. Average recall increased to 70 . Only words from citing statements published within a year of the cited papers were used. The retrieval effect of citing statement words alone (published within a year) without index or abstract terms was the following: average recall was 40 . When just the words of the titles of the cited papers were added to those citing statement words, average recall increased to 50 .