Download presentations / posters / papers
Keynotes (abstracts):
Dr. Fadi Biadsy from Google Research New York will talk about speech to text with emphasis on Hebrew and Arabic.Dr. Guy Hoffman from IDC will talk about human-robot interaction.
Dr. Yoelle Maarek from Yahoo! Labs will talk about "Queries and Questions in Yahoo! Answers"
See the posters
Tentative Schedule:
09:00 - 09:30
Coffee and registration
09:30 - 09:40
Opening words and annoucements
09:40 - 10:40
Short talks
| Oren Melamud (BIU) | A Two Level Model for Context Sensitive Inference Rules |
| Tal Baumel (BGU) | Query-Chain Focused Summarization |
| Abel Browarnik (TAU) | Ontology Learning- departing from the ontology layer cake |
10:40 - 10:55
Coffee Break
10:55 - 11:55
Keynote talk
| Dr. Yoelle Maarek (Yahoo! Labs) Queries and Questions in Yahoo! Answers |
11:55 - 13:30
Short talks
| Esther Goldbraich | IBM | Leveraging NLP to understand deviations from Clinical Practice Guidelines |
| Amnon Lotan | BIU | TruthTeller: Annotating Predicate Truth |
| Oren Tsur | HUJI | Don’t Let Me Be #Misunderstood: Predicting User Word Preferences According to Cognitive, Physical and Domain Constraints |
| Fiana Raiber | TECH | Content-Based Relevance Estimation on the Web Using Inter-Document Similarities |
| Effi Levi | NITE | NiteRater: a Framework for Automated Scoring of Essays in Hebrew |
13:30 - 14:45
Lunch + Poster (Lobby)
14:45 - 15:45
Keynote talk
| Dr. Guy Hoffman (IDC) Human-Robot Interaction and Collaboration |
15:45 - 16:10
Coffee Break
16:10 - 17:10
Keynote talk
| Dr. Fadi Biadsy (Google Research NY) GOOGLE’S VOICE SEARCH - FOCUSING ON ARABIC AND HEBREW |
17:10 - 17:15
Closing Remarks
17:15
End of ISCOL
Dr. Yoelle Maarek from Yahoo! Labs will talk about "Queries and Questions in Yahoo! Answers":
With the expansion of Web search engines, users have learned to stop
asking proper natural-language questions (e.g., "What is the height of
Corcovado?"), in favor of issuing queries (e.g., "height of Corcovado").
This transition has been driven by users becoming aware that search
engines would not "understand" their questions, but rather attempt at
locating Web pages that match, perfectly or approximately, their query
phrase. Queries have somehow developed their own characteristics and have
been shown to follow their own language model. Still, users do not see
their needs always satisfied by search engines. This happens in three
cases, either (1) the search engine did not succeed in properly accessing,
indexing or retrieving relevant content, or (2) the issued query did not
adequately represent the users' needs, or, finally, (3) relevant content
does not exist yet for this specific need. Community-question answering
sites have been devised to precisely address this third issue, as they
allow users to turn to other users in order to get their needs addressed.
In the latter case, searchers revert to askers: as they communicate with
human beings, rather than machines, they become more verbose and express
their needs as real questions. In this talk, we discuss the evolving
relationship between questions and queries on the Web, how they differ and
complement each other, and how users or machines have gone back and forth
between these two forms of expressing a user's need. We show, in a typical
application of big data analysis, how query logs, question logs and more
interestingly query-to-question logs can be mined to bring new insights,
and support new features to assist users in their quest for information. Dr. Guy Hoffman from IDC:Abstracts
Title: Human-Robot Interaction and Collaboration
Within decades, robots are expected to enter homes, offices, schools, and nursing facilities, and we should expect them even sooner in operating rooms, battlefields, construction sites, and repair shops. Successful human-robot interaction design is key to enable these robots to work smoothly and intuitively with untrained human partners. This challenge has led to the emerging field of Human-Robot Interaction (HRI) research, investigating computational, cognitive, and design approaches to human-adaptive robots, and evaluating people's responses to such robots.
This talk gives an overview of seminal and current HRI research, as well as my own research in human-robot collaboration. I discuss the design of non-verbal behaviors such as turn-taking, gaze, and gestures for shared attention, which we have implemented on an expressive humanoid robot, and how it impacts joint task performance between a human and a robot. In another project, we evaluate the role of anticipation of the human's actions, showing effects on team performance, as well as on the human partner's sense of the robot's trustworthiness and commitment. I then describe an embodied cognitive framework for robots, based on a model of perceptual simulation and cross-modal reinforcement, demonstrating how this model supports physical practice in an ensemble, and its effects on human subjects. For example, we see effects on the perception of the robot's intelligence, credit, and even gender, but also the induction of stress and self-deprecation.
In the field of entertainment robotics, I present a robotic theater control system using insights from acting theory, which enables robotic nonverbal behavior that is both reactive and expressive. I then discuss an interactive robotic Jazz improvisation system that uses embodied gestures for musical expression, enabling simultaneous, yet responsive, joint improvisation.
Finally, I present the design of a smartphone-based media companion robot. Human-subject studies show effects on music enjoyment and social presence when the robot responds to music that participants listen to, but no apparent sensitivity to the beat-alignment of the robot's motion.
Title: GOOGLE’S VOICE SEARCH - FOCUSING ON ARABIC AND HEBREW
Google voice search has changed the way users interact with their devices. Users speak their search queries and questions, typically using a mobile phone, and the system returns transcriptions, answers, and web search results. In this talk, I will describe Google’s voice search system. I will focus on the automatic speech recognition problems specific to Arabic and Hebrew, such as lack of diacritization/nikud and support for multiple Arabic dialects. We will compare recognizers for ?ve Arabic dialects with the potential to reach more than 125 million people in Egypt, Jordan, Lebanon, Saudi Arabia, the United Arab Emirates (UAE), and 7 million people in Israel. We compare systems built on diacritized vs. non-diacritized text, and show results of cross-dialect experiments.
Posters
| Ofer Bronstein | BIU | Textual Entailment with Variables |
| Gitit Kehat | TAU | Statistical transliteration of Judeo Arabic |
| Oleg Rokhlenko | Yahoo! | Generating Synthetic Comparable Questionsfor News Articles |
| Asher Stern | BIU | An Application-Oriented Task and Dataset for Implicit Argument Recognition |
| Lili Kotlerman | BIU | Sentence Clustering via Projection over Term Clusters |
| Iddo Aviram | BGU | LDA with Redundancy |
| Iddo Aviram | BGU | Effective Topic Modeling for Query Retreival |
| Avihai Mejer | Yahoo! | From Query to Question in One Click: Suggesting Synthetic Questions to Searchers |
| Naama Twitto–Shmuel | Haifa | Improving Statistical Machine Translation by Automatic Identifcation of Translationese |
| Nir Ofek | BGU | Unsupervised Methodology for Context-Level Sentiment Analysis |
| Marina Litvak | SCE | Cross-lingual training of summarization systems using annotated corpora in a foreign language |
| Marina Litvak | SCE | Mining the Gaps: Towards Polynomial Summarization |
| Chaya Liebeskind | BIU | Statistical Thesaurus Construction for a Morphologically Rich Language |
| Kfir Bar | TAU | Automatic Arabic Multiword Expression Boundary Detection |
| Dror Mughaz | BIU | Estimating the Birth and Death Years of Authors of Undated Documents using Undated Citationsþ |
| Raphael Cohen | BGU | Towards Understanding of Medical Hebrew |
| Gabriel Stanovsky | BGU | Hebrew Paraphrase Recognition Using Deep Learning Architecture |
| Erel Segal Halevi | BIU | Textual Entailment - from Single Hypotheses to Grammar-Based Hypotheses Setsþ |
| Tomer Hasid | TAU | Statistical Analysis of Orthographic Variationþ |
| Reut Tsarfaty | Weizmann | A Unified Dependency Scheme for Automatic Morpho-Syntactic Analysisþ |
| Elena Even-Simkin | BGU | The Application of Iconic and Systematic Character of 'Irregular'Forms for Computational Language Programsþ |
Download - Papers / Presentations
| Marina Litvak | Polytope model for extractive summarization |
| Marina Litvak | Cross-lingual training of summarization systems using annotated corpora in a foreign language |
| Amnon Lotan | TruthTeller: Annotating Predicate Truth |
| Abel Browarnik | Ontology Learning departing from the ontology layer cake |
| Naama Twitto–Shmuel | Improving Statistical Machine Translation by Automatic Identifcation of Translationese |
| Raphael Cohen | Towards Understanding of Medical Hebrew |
| Iddo Aviram | Effective Topic Modeling for Query Retreival |
| Gabriel Stanovsky | Hebrew Paraphrase Recognition Using Deep Learning Architecture |
| Oren Melamud | A Two Level Model for Context Sensitive Inference Rules (paper,presentation) |
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