I propose to fashion this paper after the pattern of a conventional sermon. That is, I shall begin by taking a text, and shall then elaborate on it. My text is a sentence of Whitehead, and it reads as follows: “It is more important that a proposition be interesting than that it be true; the importance of truth is that it adds to interest.” To my knowledge Whitehead makes this identical remark at least twice in his writings. It appears in (...) Process and Reality . And it appears again, word for word, several years later in Adventures of Ideas . The fact that he thus says it twice, in identical words, suggests to me that he is himself immensely pleased with it, and that he values highly the thought which it expresses. At this I am not at all surprised. For it seems to me that the remark enshrines one of those sudden flashes of insight for which Whitehead is famous, and which stamp him as, not merely the ordinary very clever or very learned man, but the man of genius. Speaking for myself, I can record that when I first read this remark it produced in me a sudden thrill, a sense of illumination, of the opening of new vistas, not wholly dissimilar to the thrill which, as a very young man, one felt when one first read certain stanzas of Shelley or Wordsworth. (shrink)

There is a practical five-step method of ethics dialog developed by John Woolman, an 18th c. businessman and ethical activist, that was used by Robert K. Greenleaf, a 20th c. A.T.&T. Corporate Vice-President, that includes: (a) friendly, emotive affect; (b) discussion of mutual commonalities; (c) discussion of issue entanglements; (d) discussion of potential experimental solutions; and, (e) trial and feedback discussion. This method of dialog appears to proceed with a type of consciousness considered by John Woolman and Bernard Lonergan as (...) one where the I is conscious that I and Others are part of a more foundational, larger and prior We. This type of dialog is different than Socratic dialog. The corresponding type of consciousness is different than the more derivative, e.g., two allies being united in their response to a common goal. It is also different than Buber's I and Thou appreciative consciounsess of the interestingness, value, diversity, and uniqueness of others. Woolman dialog as seen in four cases appears to be a concrete method that has some value both as an end in itself and as instrumental means that can: be issue effective, help build ethical organization/community culture, and help facilitate peaceful, evolutionary change and development. Limitations of the method are also considered. The method may also be a several hundred year anticipation of experiment based pragmatist philosophy that is anthropologically sensitive to cultural entanglements. No man is an Iland, intire of it selfe, ... Each is a peece of the Continent, a part of the maine.... John Donne (17th c.). (shrink)

It is normal to think that philosophers’ first dedication is to the truth. Publishers and writers consider ideas and papers according to criteria such as originality, eloquence, interestingness, soundness, and plausibility. I suggest that moral consequence should play a greater role in our choices to publish when serious harm is at stake. One’s credence in a particular idea should be weighed against the potential consequences of the publication of one’s ideas both if one turns out to be right and (...) if one turns out to be wrong. This activist approach to philosophical writing combines moral concern with epistemic humility. (shrink)

Discovering high-utility itemsets (HUIs) consists of finding sets of items that yield a high profit in customer transaction databases. An important limitation of traditional high-utility itemset mining (HUIM) is that only the utility measure is used for assessing the interestingness of patterns. This leads to finding several itemsets that have a high profit but contain items that are weakly correlated. To address this issue, this paper proposes to integrate the concept of correlation in HUIM to find profitable itemsets that (...) are highly correlated, using the all-confidence and bond measures. An efficient algorithm named FCHM (fast correlated high-utility itemset miner) is proposed to efficiently discover correlated high-utility itemsets (CHIs). Two versions of the algorithm are proposed: FCHM|$_{all\text{-}confidence}$| and FCHM|$_{bond}$|⁠, which are based on the all-confidence and bond measures, respectively. An experimental evaluation was done using four real-life benchmark datasets from the HUIM literature: mushroom, retail, kosarak and foodmart. Results show that FCHM is efficient and can prune a huge amount of weakly CHIs. (shrink)

According to the expressive view of voting, a voter derives expressive utility from casting a vote. We present two possible sources of expressive utility: social interaction with voters having the same political preferences, and interestingness of the election. First, it has been suggested that a voter's expressive utility may increase when there are more voters having the same political preference. We extend this line of study and test the hypothesis that a voter's expressive utility increases as the number of (...) voters having the same political preferences increases in the local community, where interaction occurs more frequently with others than it does with others in distant communities. Second, we propose and test the other hypothesis, that voters’ expressive utility is larger when the election is more interesting. Using 2008 parliamentary election data from Korea, where the election consists of both 245 single-member districts and only one nationwide district for proportional representatives, we find supporting evidence for these two arguments: the turnout rate is significantly and positively related to the share of proportional representation votes for the largest party in each single-member district; the turnout rate is also significantly and positively related to the number of polls for single-member district election conducted by major broadcasting companies, which we use as a proxy variable for interestingness of the election. (shrink)

His own approach to aesthetics was unusually pure. Frank Sibley wrote lapidary essays that remain models of a type of philosophical prose in which distinctions are carefully drawn, arguments are patiently developed, and a clarity of overall conception is achieved through a great economy of means. The virtues most often mentioned in connection with Sibley are those of this type of prose. But his philosophical approach was pure in another—and more substantive—sense too. Sibley characteristically investigated conceptual issues that were identifiable (...) without regard to specific aesthetic contexts. For instance, when Sibley discussed gracefulness, the particular point he had in mind could, if he so chose, be made about a vase, a line in a painting, the arch of a person’s eyebrow, or a pebble. We might think that such a procedure would severely constrain the interestingness of what an aesthetician has to say, and yet time and again Sibley shows us how much there is to gain from it. If being a phenomenologist means having a keen eye for elusive but potentially vital features of our experience, then Sibley, as a phenomenologist of the aesthetic, has no peers. (shrink)

Much research has linked surprise to violation of expectations, but it has been less clear how one can be surprised when one has no particular expectation. This paper discusses a computational theory based on Algorithmic Information Theory, which can account for surprises in which one initially expects randomness but then notices a pattern in stimuli. The authors present evidence that a “randomness deficiency” heuristic leads to surprise in such cases.

Frequent itemset mining is the most important step of association rule mining. It plays a very important role in incremental data environments. The massive volume of data creates an imminent need to design incremental algorithms for the maximal frequent itemset mining in order to handle incremental data over time. In this study, we propose an incremental maximal frequent itemset mining algorithms that integrate subjective interestingness criterion during the process of mining. The proposed framework is designed to deal with incremental (...) data, which usually come at different times. It extends FP-Max algorithm, which is based on FP-Growth method by pushing interesting measures during maximal frequent itemset mining, and performs dynamic and early pruning to leave uninteresting frequent itemsets in order to avoid uninteresting rule generation. The framework was implemented and tested on public databases, and the results found are promising. (shrink)