XML query-update independence analysis revisited

Junedi, Muhammad; Genevès, Pierre; Layaïda, Nabil

doi:10.1145/2361354.2361375

Cited by 5 publications

(3 citation statements)

References 12 publications

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“…This technique was used by Robertson and Walker [233] to enhance the Okapi BM25 ranking function [234]. Some other approaches for query reformulation are utilization of structured query [69,219,141,127], Boolean query [213,173,107,144], XML query [138,65,137] and phrase matching [14].…”

Section: Query Reformulationmentioning

confidence: 99%

“…The authors compared this technique to contemporary QE techniques and experimentally demonstrated the formers' superiority. XML queries can also be used for improving precision in IR systems for enhancing the Internet searches (e.g., [138,65,137]). Improving precision in IR systems through QE using web pages has been proposed by Cui et al [76,77] and Zhou et al [300].…”

Section: Importance Of Query Expansionmentioning

confidence: 99%

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Query expansion techniques for information retrieval: A survey

Azad

Deepak

2019

Information Processing & Management

228

104

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With the ever increasing size of the web, relevant information extraction on the Internet with a query formed by a few keywords has become a big challenge. Query Expansion (QE) plays a crucial role in improving searches on the Internet. Here, the user's initial query is reformulated by adding additional meaningful terms with similar significance. QE -as part of information retrieval (IR) -has long attracted researchers' attention. It has become very influential in the field of personalized social document, question answering, cross-language IR, information filtering and multimedia IR. Research in QE has gained further prominence because of IR dedicated conferences such as TREC (Text Information Retrieval Conference) and CLEF (Conference and Labs of the Evaluation Forum). This paper surveys QE techniques in IR from 1960 to 2017 with respect to core techniques, data sources used, weighting and ranking methodologies, user participation and applications -bringing out similarities and differences.There is a huge amount of data available on the Internet, and it is growing exponentially. This unconstrained information-growth has not been accompanied by a corresponding technical advancement in the approaches for extracting relevant information [191]. Often, a web-search does not yield relevant results. There are multiple reasons for this. First, the keywords submitted by the user can be related to multiple topics; as a result, the search results are not focused on the topic of interest. Second, the query can be too short to capture appropriately what the user is looking for. This can happen just as a matter of habit (e.g., the average size of a web search is 2.4 words [257,255]). Third, the user is often not sure about what he is looking for until he sees the results. Even if the user knows what he is searching for, he does not know how to formulate an appropriate query (navigational queries are exceptions to this [51]). QE plays an important part in fetching relevant results in the above cases. Most web queries fall under the following three fundamental categories [51, 139] :-Informational Queries: Queries that cover a broad topic (e.g., India or journals) for which there may be thousands of relevant results. -Navigational Queries: Queries that are looking for specific website or URL (e.g., ISRO).-Transactional Queries: Queries that demonstrate the user's intent to execute a specific activity (e.g., downloading papers or buying books).2 Hiteshwar Kumar Azad, Akshay DeepakCurrently, user-queries are mostly processed using indexes and ontologies, which work on exact matches and are hidden from the users. This leads to the problem of term mismatch: user queries and search index are not based on the same set of terms. This is also known as the vocabulary problem [99]; it results from a combination of synonymy and polysemy. Synonymy refers to multiple words with common meaning, e.g., "buy" and "purchase". Polysemy refers to words with multiple meanings, e.g., "mouse" (a computer device or an animal). Synonymous and polysemou...

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Section: Query Reformulationmentioning

confidence: 99%

Section: Importance Of Query Expansionmentioning

confidence: 99%

Query expansion techniques for information retrieval: A survey

Azad

Deepak

2019

Information Processing & Management

228

104

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“…We formalized the notion of query-update independence and made this notion more precise and more general. Outside the SPARQL context, the query-update independence problem has been intensively studied, in particular in the relational context [3,10] and in the setting of XML structures [2,8]. However, due to the SPARQL/RDF's open world assumption, these results do not transfer to the SPARQL context.…”

Section: Related Workmentioning

confidence: 99%

On Query-Update Independence for SPARQL

Guido

Genevès

Layaïda

et al. 2015

Proceedings of the 24th ACM International on Conference on Information and Knowledge Management

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International audienceThis paper investigates techniques for detecting independence of SPARQL queries from updates. A query is independent of an update when the execution of the update does not affect the result of the query. Determining independence is especially useful in the context of huge RDF repositories, where it permits to avoid expensive yet useless re-evaluation of queries. While this problem has been intensively studied for fragments of relational calculus, very few works exist for the standard query language for the semantic web. We report on our investigations on how a notion of independence can be defined in the SPARQL context

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