The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
taken into account when indexing documents and when performing searching. Utilizing this approach, it is possible to use a natural language to express user queries. In many cases, this way is more usual for users to describe their information needs compared to the keyword style. The factoid question answering task is one
structure from any natural language text corpus and use it to provide more relevant search results than keyword-search for specific classes of queries. Our evaluation justified significant relevance gain (20–30%) for two large Biomedical text corpora.
Computer science is in the more challenging era due to the digital growth and demand that we are facing today. A typical IR system will not go far enough as it uses keyword in order to retrieve the desired information. On the other hand, natural language question answering which is based on logic retrieval have proven
In the application of geographic data inquiry, traditional search engine put up with queries using keyword matching method mostly, which, however, can hardly get the most accurate and expected answers for users, because spatial semantic queries described by human natural language are difficult for computers to
This paper introduces the Chinese Semantic Retrieval model and the key technology. It initially points out the core idea of mapping natural language to RDF triples. Based on the Language Technology Platform dependency relationship, it classifies the Chinese question. Then, the article outlines the concrete method of
relevant to a keyword-based query can be retrieved only if they share many words. Recently, Word Embeddings emerged and tried to cope with this problem by representing words in a language as vectors in a continuous vector space. An interesting property of these vectors is that two different words with similar meaning are
, these keyword-based methods can not support spatial query very well. For example, searching documents on “debris flow took place in Hunan last year”, the documents selected in this way may only contain the words “debris flow” and “Hunan” rather than refer to “debris flow
POLARS-PAIRS was constructed for an anatomic pathology department of a university hospital. The system produced surgical pathology reports for the patient's chart and status log to monitor the progress of specimens. The educational function is served by a disease index file retrievable by natural language for a
users and game developers since these quality affects users' satisfaction and opportunity to increase market share respectively. However, manually extracting game usability qualities and problems from a large number of game reviews is challenging since most reviews often use natural language and may not be well-organized
a word-dependent system using the Arabic isolated word /ns10 as10 cs10 as10 ms10//[unk]/ a single keyword for the test utterance. This choice has been made because the word /ns10 as10 cs10 as10 ms10//[unk]/ is mostly used by the Arabic speakers. Speech features are extracted using MFCC. The HTK is used to implement the
As software systems continue to grow and evolve, locating code for software maintenance tasks becomes increasingly difficult. Source code search tools match a developer's keyword-style or natural language query with comments and identifiers in the source code to identify relevant methods that may need to be changed or
models such as a vector space model, a language model and two probabilistic models. We also proposed different measures to compute textual entailment between two terms allowing us to hopefully select appropriate keywords from thesauri to expand documents or queries automatically.
data compression, the quick keyword index, and the automatic keyword selection, are discussed. These techniques, which are based on the statistical properties of word occurrence, are fairly simple, so that the information retrieval systems employing them can be implemented with ease. The data compression technique reduces
In this paper, we show some the implementation issues of automatic speech recognition (ASR) for portable devices. First, we propose free-running speech recognition software which does not need to push the button before saying voice command and is always running for detecting key-words under real environment. Second
sense discovery problem. Given a query and a list of result pages, our unsupervised method detects word sense communities in the extracted keyword network. The documents are assigned to several refined word sense communities to form clusters. We use the modularity score of the discovered keyword community structure to
proposed a formalized model of the text semantic similarity and similarity algorithm based on the case grammar. The semantic meanings of a sentence stem decide the similarity of a sentence. To the similarity sentence, a vector is used for the decorating case to get similarity algorithm. In this way, it avoided the keyword
In this paper, cascade Chinese potential name recognition is proposed. Internal information of a person like family name, first name do not needed for name recognition while context keywords is used for name guessing. Some conceptions such as bidirectional potential name recognition, rough confirmation of potential
. This repository also contained more than 86.8 million keywords associated with the images. The key contribution of this work is that it combines clustering and natural language processing tasks to automatically create a large corpus of news images with good quality tags or meta-information so that interesting vision tasks
information is especially important. Keyword-search, a de-facto standard to search over Electronic Health Records (EHR), being simple and therefore popular technique, however, is not ideal and often returns either too many irrelevant or too few relevant search results. Clinicians, usually very short on time, just cannot afford
Clients' queries upon keywords or other informed description do not usually provide complete and unambiguous retrieval of information. Expansion of the queries based on semantic relation and phrase patterns is an effective approach to improve the retrieval. In this paper, a novel approach to queries expansion is
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.