Abstract

Abstract
The development of information retrieval algorithms and temporal information retrieval ones has been extensively carried out over the last few years. While several studies have been conducted, most of these researches relate to English, leading to a lack of knowledge in several other important languages. This includes the Persian one. In this work, we aim to shorten this gap by contributing, disseminating and enlarging the knowledge we have on temporal information retrieval aspects in Persian, which is one of the dominant languages in the Middle East, widely spoken in several countries. To achieve this objective, we propose to understand the use of temporal expressions on a large-scale Persian search engine query log consisting of 27M queries. In particular, we focus on explicit (e.g., June 2017) and relative temporal expressions (e.g., tomorrow) and try to understand (1) how often temporal expressions are used in web queries; (2) which type of temporal expressions (Date, Time, Duration and Set) are commonly used; (3) to which time (past, current or future) do temporal expressions mostly refer to; (4) to which category they often belong; (5) how often do user's reformulate their queries by adding temporal expressions; and (6) how using temporal expressions affects user's satisfaction. We believe that answering these questions may be beneficial for a large number of tasks including, user's behavior understanding and search engines' improvement effectiveness.

Abstract

Abstract
The 1st International Workshop on Narrative Extraction from Texts (Text2Story 2018) was held in conjunction with the 40th European Conference on Information Retrieval, ECIR 2018, Grenoble on the 26 th March 2018. The workshop aimed to help foster the collaboration of researchers on a wide range of multidisciplinary issues related to the text-to-narrativestructure. The program consisted of two keynote talks, six research presentations, a poster session and a slot for demo presentations. This report briefly summarizes the workshop. More information about the workshop is available at http://text2story18.inesctec.pt

Abstract
The news industry has gone through seismic shifts in the past decade with digital content and social media completely redefining how people consume news. Readers check for accurate fresh news from multiple sources throughout the day using dedicated apps or social media on their smartphones and tablets. At the same time, news publishers rely more and more on social networks and citizen journalism as a frontline to breaking news. In this new era of fastflowing instant news delivery and consumption, publishers and aggregators have to overcomea great number of challenges. These include the verification or assessment of a source's reliability; the integration of news with other sources of information; real-time processing of both news content and social streams in multiple languages, in different formats and in high volumes; deduplication; entity detection and disambiguation; automatic summarization; and news recommendation. Although Information Retrieval (IR) applied to news has been a popular research area for decades, fresh approaches are needed due to the changing type and volume of media content available and the way people consume this content. Hence, the first international workshop on recent trends in News Information Retrieval (NewsIR) was held in conjunction with ECIR 2016. As part of the workshop, we released a new dataset consisting of one million news articles to the research community. The workshop was very well attended with around 70 registered participants. We received a healthy number of 19 submissions in total of which 12 were accepted for presentation. In addition to that, we were pleased to have two keynote talks by well-known experts in the field - on with an industry background (Jochen Leidner) and one from academia (Julio Gonzalo). The workshop also included a breakout session to discuss ideas for a future data challenge in news IR and closed with a focused panel discussion to reflect on the day. Throughout the day the workshop stimulated discussions around new and powerful uses of IR applied to news sources and the intersection of multiple IR tasks to solve real user problems. In particular, several ideas were presented on solving complex information needs for media monitoring, event detection and summarisation. Moreover, and going forward, the workshop concluded with a long list of suggestions for shared tasks, and dataset requirements.

Abstract
Over the last few years, an increasing number of user's and enterprises on the internet has generated a global marketplace for both employers and job seekers. Despite the fact that online job search is now more preferable than traditional methods - leading to better matches between the job seekers and the employer's intents - there is still little insight into how online job searches are different from general web searches. In this paper, we explore the different characteristics of online job search and their differences with general searches, by leveraging search engine query logs. Our experimental results show that job searches have specific attributes which can be used by search engines to increase the quality of the search results.