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

Abstract

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.