Methods and systems for managing deployments are disclosed. A deployment may include one or more devices. The devices may include hardware and/or software components. The operation of the deployment may depend on the operation of these devices and components. To manage the operation of the deployment, a system may include a deployment manager. The deployment manager may obtain logs for components of the deployment reflecting the historical operation of these components and use the log to predict the future operation of the deployment. Based on the predictions, the deployment manager may take proactive action to reduce the likelihood of the deployment becoming impaired.

Existing research on cross-lingual retrieval cannot take good advantage of large-scale pretrained language models, such as multilingual BERT and XLM. The absence of cross-lingual passage-level relevance data for finetuning and the lack of query-document style pretraining are some of the key factors of this issue. Accordingly, embodiments of two novel retrieval-oriented pretraining tasks are presented herein to further pretrain cross-lingual language models for downstream retrieval tasks, such as cross-lingual ad-hoc retrieval (CUR) and cross-lingual question answering (CLQA). In one or more embodiments, distant supervision data was constructed from multilingual texts using section alignment to support retrieval-oriented language model pretraining. In one or more embodiments, directly finetuning language models on part of an evaluation collection was performed by making Transformers capable of accepting longer sequences. Experiments show that model embodiments significantly improve upon general multilingual language models in at least the cross-lingual retrieval setting and the cross-lingual transfer setting.

A method, an apparatus, a device and a storage medium for outputting information are provided. The method includes: acquiring a to-be-translated sentence; determining a foreign language sentence matching the to-be-translated sentence from a preset set of sentence pairs, where the set of sentence pairs includes local language sentences and corresponding foreign language sentences; determining a target foreign language sentence of the to-be-translated sentence according to the to-be-translated sentence and the determined foreign language sentence; and outputting the target foreign language sentence.

A method for conducting a cross lingual searching utilizing an ontology reference process to ensure thoroughness. When a query is entered, an ontology database is accessed to identify all representations for the parent entity of interest within specified languages. These representations are used to form a search set that results in more thorough collection from the data sources. Thus, the disclosed method accommodates situations where languages do not follow the same construct (e.g. English compared to Chinese) and where direct translation does not adequately represent the intent of the user's inquiry.

An electronic device includes a processor and a memory to store a dictionary and index information. The memory can store instructions to cause the processor to: extract a first text in a first language included in data; determine whether or not a transliteration pair is included in the dictionary; if the transliteration pair is identified, index the first text and at least one second text to the data and store same in the index information; and, if the transliteration pair is not identified, extract at least one third text in the second language by inputting the extracted first text to a machine learning model for transliterating an input in the first language into the second language and extracting same, and index the first text and the at least one third text which has been extracted to the data and store same in the index information.

The present disclosure generally relates to decoding encoded files. More particularly, the present disclosure relates to systems and processes for determining the underlying language of encoded files having certain file formats with an undeterminable encoding. It may be difficult, time consuming, and costly to decode the files with undeterminable encodings as such files may require the language to be identified prior to decoding. Embodiments disclosed herein relate to determining the underlying language of the files by analyzing bit sequences in the encoded file and comparing the bit sequences against training data to determine matching patterns between the bit sequences in the file and the bit sequences known correspond to terms associated with a particular language.

A method, computer program product, and system for providing cross-lingual search results that retain cultural context include a processor(s) monitoring (with user permission) computing activities performed by the user, via a client. The processor(s) analyzes the computing activities to identify data comprising elements relevant to the user and relationships between the elements and the user. The processor(s) generates a data structure comprising the data. The processor(s) generates a search interface for obtaining entries in a first language to perform a query; the entries are search parameters embedded with a portion of the elements. The processor(s) obtains an entry in the first language. The processor(s) extracts the portion of the elements from the entry (cultural context for the entry). The processor(s) determines target languages for data responsive to the query. The processor(s) translates the search parameters and the cultural context into the target languages and executes searches on databases.

Multilingual/cross-region search result merging is described. In various examples, a user enters a query to an information retrieval system and receives search results appropriate to different combinations of human language and geographical region, and where the combinations are selected according to features describing intent of the query. In examples, query intent features are computed using a query understanding component (e.g. a trained query intent classifier) and used, optionally with other query features, to identify combinations of human language and geographical region from a stored profile. In examples the stored profile is computed using data about documents available to an information retrieval system and data about past search behavior. In examples, different combinations of language and region are used to retrieve search results which are merged. For example, a query is translated into another language while preserving calculated intent features of the query.

Approaches for translating a transliterated search query are provided. An approach includes receiving a search query containing a transliterated word. The approach also includes determining a source language corresponding to the transliterated word. The approach further includes converting the transliterated word to a word in the source language. The approach additionally includes translating the word in the source language to a word in a target language. The approach also includes performing a search using the word in the target language.

A system provides a mechanism for providing a multi-brand experience. The system provides a way implement a multi-brand experience by adding a layer of information that can be helpful when differentiating among consumers in order to accomplish market segmentation. The multi-brand experience enables each group of users to be presented with a different look and feel of the same application.