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Zhongyuan Wang and Haixun Wang

Billions of short texts are produced everyday, in the form of search queries, ad keywords, tags, tweets, messenger conversations, social network posts, etc. Unlike documents, short texts have some unique characteristics which make them difficult to handle. First, short texts, especially search queries, do not always observe the syntax of a written language. This means traditional NLP techniques, such as syntactic parsing, do not always apply to short texts. Second, short texts contain limited context....

Publication details
Date: 1 August 2016
Type: Inproceeding
Masrour Zoghi, Tomáš Tunys, Lihong Li, Damien Jose, Junyan Chen, Chun Ming Chin, and Maarten de Rijke
Publication details
Date: 1 July 2016
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Royi Ronen, Gal Lavee, and Elad Yom-Tov

Collaborative filtering (CF) recommendation systems are one of the most popular and successful methods for recommending products to people. CF systems work by finding similarities between different people according to their past purchases, and using these similarities to suggest possible items of interest. Here we investigate how CF systems can be enhanced using Internet browsing data and search engine query logs, both of which represent a rich profile of individuals’ interests. We introduce two...

Publication details
Date: 16 May 2016
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Marta E. Cecchinato, Abigail Sellen, Milad Shokouhi, and Gavin Smyth

Email is far from dead; in fact the volume of messages exchanged daily, the number of accounts per user, and the number of devices on which email is accessed have been constantly “Email growing. Most previous studies on email have focused on management and retrieval behaviour within a single account and on a single device. In this paper, we examine how people retrieve email in today’s ecosystem through an in-depth qualitative diary study with 16 participants. We found that personal and work accounts are...

Publication details
Date: 1 May 2016
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Jaime Teevan, Shamsi Iqbal, Carrie J. Cai, Jeffrey P. Bigham, Michael S. Bernstein, and Elizabeth M. Gerber

It is difficult to accomplish meaningful goals with limited time and attentional resources. However, recent research has shown that concrete plans with actionable steps allow people to complete tasks better and faster. With advances in techniques that can decompose larger tasks into smaller units, we envision that a transformation from larger tasks to smaller microtasks will impact when and how people perform complex information work, enabling efficient and easy completion of tasks that currently seem...

Publication details
Date: 1 May 2016
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Jaime Teevan

I found it hard to start writing this document, and put it off until the last possible moment. Complex tasks like writing are difficult to do because they seem to require long, uninterrupted periods of deep engagement to make meaningful progress. My goal is to change this. My colleagues and I exploring the idea of selfsourcing as a way to help people easily perform large personal information tasks by breaking them all the way down into microtasks that only take a few seconds each to complete....

Publication details
Date: 1 May 2016
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Jaime Teevan, Shamsi T. Iqbal, and Curtis von Veh

This paper presents the MicroWriter, a system that decomposes the task of writing into three types of microtasks to produce a single report: 1) generating ideas, 2) labeling ideas to organize them, and 3) writing paragraphs given a few related ideas. Because each microtask can be completed individually with limited awareness of what has been already done and what others are doing, this decomposition can change the experience of collaborative writing. Prior work has used microtasking to support...

Publication details
Date: 1 May 2016
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Eric Nalisnick, Bhaskar Mitra, Nick Craswell, and Rich Caruana

This paper investigates the popular neural word embedding method Word2vec as a source of evidence in document ranking. In contrast to NLP applications of word2vec, which tend to use only the input embeddings, we retain both the input and the output embeddings, allowing us to calculate a different word similarity that may be more suitable for document ranking. We map the query words into the input space and the document words into the output space, and compute a relevance score by aggregating the cosine...

Publication details
Date: 11 April 2016
Type: Inproceeding
Publisher: WWW – World Wide Web Consortium (W3C)
Sandro Bauer, Filip Radlinski, and Ryen W. White

People commonly need to purchase things in person, from large garden supplies to home decor. Although modern search systems are very effective at finding online products, little research attention has been paid to helping users find places that sell a specific product offline. For instance, users searching for an apron are not typically directed to a nearby kitchen store by a standard search engine.

In this paper, we investigate "where can I buy"-style queries related to...

Publication details
Date: 1 April 2016
Type: Inproceeding
Publisher: WWW – World Wide Web Consortium (W3C)
Publication details
Date: 1 April 2016
Type: Inproceeding
Publication details
Date: 1 April 2016
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Publication details
Date: 1 April 2016
Type: Inproceeding
Publisher: WWW – World Wide Web Consortium (W3C)
Zhiyi Luo, Yuchen Sha, Kenny Zhu, Seung-Won Hwang, and Zhongyuan Wang
Publication details
Date: 1 April 2016
Type: Inproceeding
Yun-Nung Chen, Dilek Hakkani-Tur, and Xiaodong He

The recent surge of intelligent personal assistants motivates spoken language understanding of dialogue systems. However, the domain constraint along with the inflexible intent schema remains a big issue. This paper focuses on the task of intent expansion, which helps remove the domain limit and make an intent schema flexible. A convolutional deep structured semantic model (CDSSM) is applied to jointly learn the representations for human intents and associated utterances. Then it can flexibly generate...

Publication details
Date: 1 March 2016
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
Liu Yang, Qi Guo, Yang Song, Sha Meng, Milad Shokouhi, Kieran McDonald, and W. Bruce Croft

Proactive search systems like Google Now and Microsoft Cortana have gained increasing popularity with the growth of mobile Internet. Unlike traditional reactive search systems where search engines return results in response to queries issued by the users, proactive systems actively push information cards to the users on mobile devices based on the context around time, location, environment (e.g., weather), and user interests. A proactive system is a zero-query information retrieval system, which makes...

Publication details
Date: 1 March 2016
Type: Inproceeding
Rishiraj Saha Roy, Anusha Suresh, Niloy Ganguly, and Monojit Choudhury

In this research, we explore nested or hierarchical query segmentation4, where segments are defined recursively as consisting of contiguous sequences of segments or query words, as a more effective representation of a query. We design a lightweight and unsupervised nested segmentation scheme, and propose how to use the tree arising out of the nested representation of a query to improve ranking performance. We show that nested segmentation can lead to significant gains over stateof-the-art at...

Publication details
Date: 1 March 2016
Type: Inproceeding
Publisher: ECIR
Zhaohui Wu, Yang Song, and C. Lee Giles

Continuously discovering novel entities in news and Web data is important for Knowledge Base (KB) maintenance. One of the key challenges is to decide whether an entity mention refers to an in-KB or out-of-KB entity. We propose a principled approach that learns a novel entity classifier by modeling mention and entity representation into multiple feature spaces, including contextual, topical, lexical, neural embedding and query spaces. Different from most previous studies that address novel entity...

Publication details
Date: 1 February 2016
Type: Inproceeding
Publisher: AAAI - Association for the Advancement of Artificial Intelligence
Bo Wu, Tao Mei, Wen-Huang Cheng, and Yongdong Zhang

Time information plays a crucial role on social media popularity. Existing research on popularity prediction, effective though, ignores temporal information which is highly related to user-item associations and thus often results in limited success. An essential way is to consider all these factors (user, item, and time), which capture the dynamic nature of photo popularity. In this paper, we present a novel approach to factorize the popularity into user-item context and time-sensitive context for...

Publication details
Date: 1 February 2016
Type: Inproceeding
Publisher: AAAI - Association for the Advancement of Artificial Intelligence
Milan Vojnovic and Se-Young Yun

We consider a team selection problem that requires to hire a team of individuals that maximizes a profit function defined as difference of the utility of production and the cost of hiring. We show that for any monotone submodular utility of production and any increasing cost function of the team size with increasing marginal costs, a natural greedy algorithm guarantees a 1 − log(a)/(a − 1)– approximation when a ≤ e and a 1 − a/e(a − 1)–approximation when a ≥ e, where a is the ratio of the utility of...

Publication details
Date: 1 February 2016
Type: Technical report
Publisher: Microsoft Research
Number: MSR-TR-2016-7
Yubin Kim, Kevyn Collins-Thompson, and Jaime Teevan

Despite technological advances, algorithmic search systems still have difficulty with complex or subtle information needs. For example, scenarios requiring deep semantic interpretation are a challenge for computers. People, on the other hand, are well-suited to solving such problems. As a result, there is an opportunity for humans and computers to collaborate during the course of a search in a way that takes advantage of the unique abilities of each. While search tools that rely on human intervention...

Publication details
Date: 1 January 2016
Type: Article
Publisher: ACM – Association for Computing Machinery
Nick Greer, Jaime Teevan, and Shamsi Iqbal

This paper provides a brief introduction to opportunities that exist for providing better technological support for writing. Developing the appropriate technology that adequately supports the complex processes of writing is difficult because writing requires fundamental but varied skills such as reading, analysis, reasoning, and communication. For this reason, we believe that writing tools designed to support these skills can provide a valuable lens by which to understand and explore interesting...

Publication details
Date: 1 January 2016
Type: Technical report
Publisher: Microsoft Research
Number: MSR-TR-2016-1
Rishiraj Saha Roy, Anusha Suresh, Niloy Ganguly, Monojit Choudhury, Deepak Shankar, and Tanwita Nimiar

Past work on query segmentation has exclusively focused on at or non-hierarchical segmentation, where query words are simply partitioned into non-overlapping contiguous chunks of words. Such an approach suffers from the problem of granularity, and consequent difficulties in IR application. Here, we explore nested or hierarchical query segmentation, where segments are defined recursively as consisting of contiguous sequences of segments or query words, as an effective and powerful alternative...

Publication details
Date: 31 December 2015
Type: Technical report
Publisher: Microsoft Research
Number: MSR-TR-2015-91
Alistair Moffat, Peter Bailey, Falk Scholer, and Paul Thomas

A large number of metrics have been proposed to measure the effectiveness of information retrieval systems. Here we provide a detailed explanation of one recent proposal, INST, articulate the various properties that it embodies, and describe a number of pragmatic issues that need to be taken in to account when writing an implementation. The result is a specification for a program inst_eval for use in TREC-style IR experimentation.

Publication details
Date: 8 December 2015
Type: Inproceeding
Publisher: ACM – Association for Computing Machinery
Paul Thomas, Peter Bailey, Alistair Moffat, and Falk Scholer

Information retrieval systems are often evaluated through the use of effectiveness metrics. In the past, the metrics used have corresponded to fixed models of user behavior, presuming, for example, that the user will view a predetermined number of items in the search engine results page, or that they have a constant probability of advancing from one item in the result page to the next. Recently, a number of proposals for models of user behavior have emerged that are parameterized in terms of the number...

Publication details
Date: 2 December 2015
Type: Inproceeding
Publisher: Springer
Yun-Nung Chen, Dilek Hakkani-Tur, and Xiaodong He

The recent success of voice interaction with smart devices (humanmachine genre) and improvements in speech recognition for conversational speech show the possibility of conversation-related applications. This paper investigates the task of actionable item detection in meetings (human-human genre), where the intelligent assistant dynamically provides the participants access to information (e.g. scheduling a meeting, taking notes) without interrupting the meetings. A convolutional deep structured semantic...

Publication details
Date: 1 December 2015
Type: Inproceeding
Publisher: IEEE – Institute of Electrical and Electronics Engineers
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