Content Analysis of Presidential Speeches: Term to Term Changes

This essay aims to show how American presidential Inaugural Addresses change throughout presidencies, and analyzes whether or not those changes are indicative of an evolution throughout the presidency itself. Within this research, an analysis will be done on the Inaugural Addresses for the first and second terms of both President George W. Bush and President Barack Obama. This study discusses possible reasons why changes may occur from the first term of a presidency to the second term, and, if there are indeed noticeable changes, what those changes could mean on a larger scale. Possible changes that could be seen include the topics mentioned, the tone in which they are mentioned, and how willing they are to discuss partisan and controversial ideas. This analysis will be done through a content analysis of each Inaugural Address for the above presidents, looking for mentions of religion, country, unity, economy, and war. The hypothesis behind this research is that the Inaugural Address of a first term president will be more likely to contain content aimed at attracting votes for the next election, while the Inaugural Address of a second term president will likely have more insight into the personal views of the president, as they are no longer trying to attract new votes

End-to-End Neural Ad-hoc Ranking with Kernel Pooling

This paper proposes K-NRM, a kernel based neural model for document ranking. Given a query and a set of documents, K-NRM uses a translation matrix that models word-level similarities via word embeddings, a new kernel-pooling technique that uses kernels to extract multi-level soft match features, and a learning-to-rank layer that combines those features into the final ranking score. The whole model is trained end-to-end. The ranking layer learns desired feature patterns from the pairwise ranking loss. The kernels transfer the feature patterns into soft-match targets at each similarity level and enforce them on the translation matrix. The word embeddings are tuned accordingly so that they can produce the desired soft matches. Experiments on a commercial search engine's query log demonstrate the improvements of K-NRM over prior feature-based and neural-based states-of-the-art, and explain the source of K-NRM's advantage: Its kernel-guided embedding encodes a similarity metric tailored for matching query words to document words, and provides effective multi-level soft matches

Jamie L. Bryant in a Senior Trumpet Recital

This is the program for the senior trumpet recital of Jamie L. Bryant held on October 25, 1996, in Mabee Fine Arts Center\u27s McBeth Recital Hall. Russell Hodges accompanied on organ and piano

Triggering social interactions:chimpanzees respond to imitation by a humanoid robot and request responses from it

Even the most rudimentary social cues may evoke affiliative responses in humans and promote socialcommunication and cohesion. The present work tested whether such cues of an agent may also promotecommunicative interactions in a nonhuman primate species, by examining interaction-promoting behavioursin chimpanzees. Here, chimpanzees were tested during interactions with an interactive humanoid robot, whichshowed simple bodily movements and sent out calls. The results revealed that chimpanzees exhibited twotypes of interaction-promoting behaviours during relaxed or playful contexts. First, the chimpanzees showedprolonged active interest when they were imitated by the robot. Second, the subjects requested ‘social’responses from the robot, i.e. by showing play invitations and offering toys or other objects. This study thusprovides evidence that even rudimentary cues of a robotic agent may promote social interactions inchimpanzees, like in humans. Such simple and frequent social interactions most likely provided a foundationfor sophisticated forms of affiliative communication to emerge